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An Improved Variant of Multi-Population Cooperative Constrained Multi-Objective Optimization(MCCMO)for Multi-Objective Optimization Problem 认领 引用
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作者 Muhammad Waqar Khan Adnan Ahmed Siddiqui Syed Sajjad Hussain Rizvi 《Computers, Materials & Continua》 SCIE EI 2026年第2期1874-1888,共15页
The multi-objective optimization problems,especially in constrained environments such as power distribution planning,demand robust strategies for discovering effective solutions.This work presents the improved variant... The multi-objective optimization problems,especially in constrained environments such as power distribution planning,demand robust strategies for discovering effective solutions.This work presents the improved variant of the Multi-population Cooperative Constrained Multi-Objective Optimization(MCCMO)Algorithm,termed Adaptive Diversity Preservation(ADP).This enhancement is primarily focused on the improvement of constraint handling strategies,local search integration,hybrid selection approaches,and adaptive parameter control.Theimproved variant was experimented on with the RWMOP50 power distribution systemplanning benchmark.As per the findings,the improved variant outperformed the original MCCMO across the eleven performance metrics,particularly in terms of convergence speed,constraint handling efficiency,and solution diversity.The results also establish that MCCMOADP consistently delivers substantial performance gains over the baseline MCCMO,demonstrating its effectiveness across performancemetrics.The new variant also excels atmaintaining the balanced trade-off between exploration and exploitation throughout the search process,making it especially suitable for complex optimization problems in multiconstrained power systems.These enhancements make MCCMO-ADP a valuable and promising candidate for handling problems such as renewable energy scheduling,logistics planning,and power system optimization.Future work will benchmark the MCCMO-ADP against widely recognized algorithms such as NSGA-Ⅱ,NSGA-Ⅲ,and MOEA/D and will also extend its validation to large-scale real-world optimization domains to further consolidate its generalizability. 展开更多
关键词 MCCMO algorithms adaptive diversity preservation RWMOP50 power distribution system multi-modal multi objective optimization evolutionary algorithm multi objective problem
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Machine Learning‐Driven Predictive Modeling and Multi‐Objective Exploration of Oxaliplatin‐Loaded Nanocarriers for Enhanced Loading and Encapsulation Efficiency 认领 引用
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作者 Abbas Rahdar Maryam Shirzad +1 位作者 Sonia Fathi‐Karkan M.Ali Aboudzadeh 《Materials Genome Engineering Advances》 CAS CSCD 2026年第2期75-85,共11页
Oxaliplatin(OXA),a critical third‐generation platinum chemotherapeutic,is significantly limited by suboptimal loading capacity and encapsulation efficiency in nanoparticle‐based delivery systems.To address this,we d... Oxaliplatin(OXA),a critical third‐generation platinum chemotherapeutic,is significantly limited by suboptimal loading capacity and encapsulation efficiency in nanoparticle‐based delivery systems.To address this,we developed an integrated machine learning(ML)and multi‐objective optimization(MOO)framework for the simultaneous prediction and exploration of loading efficiency(LE)and encapsulation efficiency(EE).Ensemble learning models,trained on a curated dataset of 70 experimentally characterized nanocarrier formulations,demonstrated robust predictive performance under stringent leave‐one‐paper‐out(LOPO)cross‐validation(R2=0.87 for LE,R2=0.84 for EE).The multi‐objective exploration identified a Pareto‐optimal design space,with predicted performance reaching up to 45.3%LE and 87.2%EE,and pinpointed a balanced knee‐point formulation at 40.2%LE and 83.7%EE.Interpretable ML analysis revealed surface area‐to‐volume ratio,coordination site availability,and zeta potential as the primary physicochemical drivers of OXA loading and retention.Consequently,an optimized nanocarrier profile,characterized by a particle size of 90-110 nm,a negative surface charge,and a carboxylate‐rich composition,was derived.This study establishes a predictive,data‐driven computational framework that bridges the gap between single‐objective prediction and the holistic design of high‐performance nanocarriers,providing a rational blueprint for accelerating the development of more effective OXA‐based nanotherapies for colorectal cancer. 展开更多
关键词 encapsulation efficiency|loading efficiency|machine‐learning|multi‐objective optimization|oxaliplatin
A Robust Damage Identification Method Based on Modified Holistic Swarm Optimization Algorithm and Hybrid Objective Function 认领 引用
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作者 Xiansong Xie Xiaoqian Qian 《Structural Durability & Health Monitoring》 EI 2026年第2期235-259,共25页
Correlation function of acceleration responses-based damage identificationmethods has been developed and employed,while they still face the difficulty in identifying local orminor structural damages.To deal with this ... Correlation function of acceleration responses-based damage identificationmethods has been developed and employed,while they still face the difficulty in identifying local orminor structural damages.To deal with this issue,a robust structural damage identification method is developed,integrating a modified holistic swarm optimization(MHSO)algorithm with a hybrid objective function.The MHSO is developed by combining Hammersley sequencebased population initialization,chaotic search around the worst solution,and Hooke-Jeeves pattern search around the best solution,thereby improving both global exploration and local exploitation capabilities.A hybrid objective function is constructed by merging acceleration correlation function-based and strain correlation function-based objective functions,effectively leveraging the complementary sensitivities of global and local responses.To further suppress spurious solutions and promote sparsity in parameter estimation,an additional L0.5 regularization term is introduced.The effectiveness of the proposed method is validated through numerical simulations on a simply supported beam and a steel girder benchmark structure.Comparative studies with sequential quadratic programming,genetic algorithm,andHSO demonstrate that theMHSOachieves superior accuracy and convergence efficiency,even with limited sensors and 20%noise-contaminated measurements.Results highlight that the hybrid objective function significantly enhances the detection of both major and minor damages,while the inclusion of sparse regularization improves robustness against noise and model uncertainties.The findings indicate that the proposed framework provides a reliable and computationally efficient solution for simultaneous localization and quantification of structural damages,offering promising applicability to real-world structural health monitoring scenarios. 展开更多
关键词 Damage identification holistic swarm optimization algorithm combined correlation function hybrid objective function sparse regularization grid structure
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Multi-objective ANN-driven genetic algorithm optimization of energy efficiency measures in an NZEB multi-family house building in Greece 认领 引用
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《建筑节能（中英文）》 CAS 2026年第2期62-62,共1页
The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measu... The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measures in a multi-family house building in Greece.The energy efficiency measures include different heating/cooling systems(such as low-temperature and high-temperature heat pumps,natural gas boilers,split units),building envelope components for floor,walls,roof and windows of variable heat transfer coefficients,the installation of solar thermal collectors and PVs.The calculations of the building loads and investment and operating and maintenance costs of the measures are based on the methodology defined in Directive 2010/31/EU,while economic assumptions are based on EN 15459-1 standard.Typically,multi-objective optimization of energy efficiency measures often requires the simulation of very large numbers of cases involving numerous possible combinations,resulting in intense computational load.The results of the study indicate that ANN-driven GA methods can be used as an alternative,valuable tool for reliably predicting the optimal measures which minimize primary energy consumption and life cycle cost of the building with greatly reduced computational requirements.Through GA methods,the computational time needed for obtaining the optimal solutions is reduced by 96.4%-96.8%. 展开更多
关键词 energy efficiency measures gas boilerssplit units building envelope components energy efficiency economic performance artificial neural network ann driven multi objective optimization economic performance optimization ANN driven GA methods
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Multi-objective optimization of grinding process parameters for improving gear machining precision 认领 引用 被引量：4
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作者 YOU Tong-fei HAN Jiang +4 位作者 TIAN Xiao-qing TANG Jian-ping LU Yi-guo LI Guang-hui XIA Lian 《Journal of Central South University》 SCIE EI CAS CSCD 2025年第2期538-551,共14页
The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can caus... The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can cause changes in cutting force/heat,resulting in affecting gear machining precision.Therefore,this paper studies the effect of different process parameters on gear machining precision.A multi-objective optimization model is established for the relationship between process parameters and tooth surface deviations,tooth profile deviations,and tooth lead deviations through the cutting speed,feed rate,and cutting depth of the worm wheel gear grinding machine.The response surface method(RSM)is used for experimental design,and the corresponding experimental results and optimal process parameters are obtained.Subsequently,gray relational analysis-principal component analysis(GRA-PCA),particle swarm optimization(PSO),and genetic algorithm-particle swarm optimization(GA-PSO)methods are used to analyze the experimental results and obtain different optimal process parameters.The results show that optimal process parameters obtained by the GRA-PCA,PSO,and GA-PSO methods improve the gear machining precision.Moreover,the gear machining precision obtained by GA-PSO is superior to other methods. 展开更多
关键词 worm wheel gear grinding machine gear machining precision machining process parameters multi objective optimization
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An Objective Synoptic Analysis Technique for the Identification of Tropical Cyclone Remote Precipitation in China and Its Application 认领 引用 被引量：2
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作者 JIA Li DING Chenchen +2 位作者 CONG Chunhua REN Fumin LIU Yanan 《Journal of Ocean University of China》 SCIE CAS CSCD 2025年第1期13-30,共18页
At present,the identification of tropical cyclone remote precipitation(TRP)requires subjective participation,leading to inconsistent results among different researchers despite adopting the same identification standar... At present,the identification of tropical cyclone remote precipitation(TRP)requires subjective participation,leading to inconsistent results among different researchers despite adopting the same identification standard.Thus,establishing an objective identification method is greatly important.In this study,an objective synoptic analysis technique for TRP(OSAT_TRP)is proposed to identify TRP using daily precipitation datasets,historical tropical cyclone(TC)track data,and the ERA5 reanalysis data.This method includes three steps:first,independent rain belts are separated,and those that might relate to TCs'remote effects are distinguished according to their distance from the TCs.Second,the strong water vapor transport belt from the TC is identified using integrated horizontal water vapor transport(IVT).Third,TRP is distinguished by connecting the first two steps.The TRP obtained through this method can satisfy three criteria,as follows:1)the precipitation occurs outside the circulation of TCs,2)the precipitation is affected by TCs,and 3)a gap exists between the TRP and TC rain belt.Case diagnosis analysis,compared with subjective TRP results and backward trajectory analyses using HYSPLIT,indicates that OSAT_TRP can distinguish TRP even when multiple TCs in the Northwest Pacific are involved.Then,we applied the OSAT_TRP to select typical TRPs and obtained the synoptic-scale environments of the TRP through composite analysis. 展开更多
关键词 tropical cyclone remote precipitation objective identification method
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Relationship between objective and subjective refraction measurements in patients with mild keratoconus 认领 引用
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作者 Masoud Khorrami-Nejad Ahmed Kamil Dakhil +3 位作者 Hesam Hashemian Masoud Sadeghi Reza Yousefi Foroozan Narooie-Noori 《International Journal of Ophthalmology(English edition)》 SCIE CAS 2025年第3期398-403,共6页
AIM:To compare objective dry retinoscopy and subjective refraction measurements in patients with mild keratoconus(KCN)and quantify any differences.METHODS:This cross-sectional study was done on 68 eyes of 68 patients ... AIM:To compare objective dry retinoscopy and subjective refraction measurements in patients with mild keratoconus(KCN)and quantify any differences.METHODS:This cross-sectional study was done on 68 eyes of 68 patients diagnosed with mild KCN.Objective dry retinoscopy using autorefractometer and subjective refraction measurements were performed.Sphere,cylinder,J0,J45,and spherical equivalent values were compared between the two techniques.RESULTS:The mean age of 68 patients with mild KCN was 21.32±5.03y(12–35y).There were 37(54.4%)males.Objective refraction yielded significantly more myopic sphere(-1.44 D vs-0.57 D),higher cylinder magnitude(-2.24 D vs-1.48 D),and more myopic spherical equivalent(-2.56 D vs-1.31 D)compared to subjective refraction(all P0.05).CONCLUSION:In patients with mild KCN,objective dry retinoscopy overestimates the degree of myopia and astigmatism compared to subjective refraction.The irregular cornea in KCN likely impacts objective measurements.Subjective refraction allows compensation for irregularity,providing a more accurate correction.When determining refractive targets,the tendency of objective methods to overcorrect should be considered. 展开更多
关键词 keratoconus objective refraction subjective refraction
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Dimensional synchronous modeling-based enhanced Kriging algorithm and adaptive Copula method for multi-objective synthetical reliability analyses 认领 引用
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作者 Cheng LU Yunwen FENG +1 位作者 Chengwei FEI Da TENG 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2025年第9期144-165,共22页
To accomplish the reliability analyses of the correlation of multi-analytical objectives,an innovative framework of Dimensional Synchronous Modeling(DSM)and correlation analysis is developed based on the stepwise mode... To accomplish the reliability analyses of the correlation of multi-analytical objectives,an innovative framework of Dimensional Synchronous Modeling(DSM)and correlation analysis is developed based on the stepwise modeling strategy,cell array operation principle,and Copula theory.Under this framework,we propose a DSM-based Enhanced Kriging(DSMEK)algorithm to synchronously derive the modeling of multi-objective,and explore an adaptive Copula function approach to analyze the correlation among multiple objectives and to assess the synthetical reliability level.In the proposed DSMEK and adaptive Copula methods,the Kriging model is treated as the basis function of DSMEK model,the Multi-Objective Snake Optimizer(MOSO)algorithm is used to search the optimal values of hyperparameters of basis functions,the cell array operation principle is adopted to establish a whole model of multiple objectives,the goodness of fit is utilized to determine the forms of Copula functions,and the determined Copula functions are employed to perform the reliability analyses of the correlation of multi-analytical objectives.Furthermore,three examples,including multi-objective complex function approximation,aeroengine turbine bladeddisc multi-failure mode reliability analyses and aircraft landing gear system brake temperature reliability analyses,are performed to verify the effectiveness of the proposed methods,from the viewpoints of mathematics and engineering.The results show that the DSMEK and adaptive Copula approaches hold obvious advantages in terms of modeling features and simulation performance.The efforts of this work provide a useful way for the modeling of multi-analytical objectives and synthetical reliability analyses of complex structure/system with multi-output responses. 展开更多
关键词 Adaptive Copula method Aeroengine turbine bladeddisc Aircraft landing gear system Correlation of multianalytical objectives Dimensional synchronous modeling-based enhanced Kriging algorithm Reliability analyses
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Nash Bargaining Solution-Based Multi-Objective Model Predictive Control for Constrained Interactive Robots 认领 引用
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作者 Minglei Zhu Jun Qi 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2025年第7期1516-1518,共3页
Dear Editor,This letter proposes a novel Nash bargaining solution-based multiobjective model predictive control(MPC)scheme to deal with the interaction force control and the path-following problem of the constrained i... Dear Editor,This letter proposes a novel Nash bargaining solution-based multiobjective model predictive control(MPC)scheme to deal with the interaction force control and the path-following problem of the constrained interactive robot.Considering the elastic interaction force model,a mechanical trade-off always exists between the interaction force and position,which means that neither force nor path following can satisfy their desired demands completely.Based on this consideration,two irreconcilable control specifications,the force object function and the position track object function,are proposed,and a new multi-objective MPC scheme is then designed. 展开更多
关键词 constrained interactive robots constrained interactive robotconsidering force path following interaction force modela interaction force control Nash bargaining solution path following problem multi objective model predictive control
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Two Performance Indicators Assisted Infill Strategy for Expensive Many⁃Objective Optimization 认领 引用
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作者 Yi Zhao Jianchao Zeng Ying Tan 《Journal of Harbin Institute of Technology(New Series)》 CAS 2025年第5期24-40,共17页
In recent years,surrogate models derived from genuine data samples have proven to be efficient in addressing optimization challenges that are costly or time⁃intensive.However,the individuals in the population become i... In recent years,surrogate models derived from genuine data samples have proven to be efficient in addressing optimization challenges that are costly or time⁃intensive.However,the individuals in the population become indistinguishable as the curse of dimensionality increases in the objective space and the accumulation of surrogate approximated errors.Therefore,in this paper,each objective function is modeled using a radial basis function approach,and the optimal solution set of the surrogate model is located by the multi⁃objective evolutionary algorithm of strengthened dominance relation.The original objective function values of the true evaluations are converted to two indicator values,and then the surrogate models are set up for the two performance indicators.Finally,an adaptive infill sampling strategy that relies on approximate performance indicators is proposed to assist in selecting individuals for real evaluations from the potential optimal solution set.The algorithm is contrasted against several advanced surrogate⁃assisted evolutionary algorithms on two suites of test cases,and the experimental findings prove that the approach is competitive in solving expensive many⁃objective optimization problems. 展开更多
关键词 expensive multi⁃objective optimization problems infill sample strategy evolutionary optimization algorithm
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Predefined-Time Distributed Optimization for Resource Allocation Problems With Time-Varying Objective Function and Constraints 认领 引用
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作者 Haotian Wu Yang Liu +1 位作者 Mahmoud Abdel-Aty Weihua Gui 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2025年第11期2353-2355,共3页
Dear Editor,This letter addresses distributed optimization for resource allocation problems with time-varying objective functions and time-varying constraints.Inspired by the distributed average tracking(DAT)approach,... Dear Editor,This letter addresses distributed optimization for resource allocation problems with time-varying objective functions and time-varying constraints.Inspired by the distributed average tracking(DAT)approach,a distributed control protocol is proposed for optimal resource allocation.The convergence to a time-varying optimal solution within a predefined time is proved.Two numerical examples are given to illustrate the effectiveness of the proposed approach. 展开更多
关键词 resource allocation distributed optimization time varying objective function optimal resource allocationthe distributed control protocol time varying constraints predefined time convergence
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A Novel Reliable and Trust Objective Function for RPL-Based IoT Routing Protocol 认领 引用
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作者 Mariam A.Alotaibi Sami S.Alwakeel Aasem N.Alyahya 《Computers, Materials & Continua》 SCIE EI 2025年第2期3467-3497,共31页
The Internet of Things (IoT) integrates diverse devices into the Internet infrastructure, including sensors, meters, and wearable devices. Designing efficient IoT networks with these heterogeneous devices requires the... The Internet of Things (IoT) integrates diverse devices into the Internet infrastructure, including sensors, meters, and wearable devices. Designing efficient IoT networks with these heterogeneous devices requires the selection of appropriate routing protocols, which is crucial for maintaining high Quality of Service (QoS). The Internet Engineering Task Force’s Routing Over Low Power and Lossy Networks (IETF ROLL) working group developed the IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) to meet these needs. While the initial RPL standard focused on single-metric route selection, ongoing research explores enhancing RPL by incorporating multiple routing metrics and developing new Objective Functions (OFs). This paper introduces a novel Objective Function (OF), the Reliable and Secure Objective Function (RSOF), designed to enhance the reliability and trustworthiness of parent selection at both the node and link levels within IoT and RPL routing protocols. The RSOF employs an adaptive parent node selection mechanism that incorporates multiple metrics, including Residual Energy (RE), Expected Transmission Count (ETX), Extended RPL Node Trustworthiness (ERNT), and a novel metric that measures node failure rate (NFR). In this mechanism, nodes with a high NFR are excluded from the parent selection process to improve network reliability and stability. The proposed RSOF was evaluated using random and grid topologies in the Cooja Simulator, with tests conducted across small, medium, and large-scale networks to examine the impact of varying node densities. The simulation results indicate a significant improvement in network performance, particularly in terms of average latency, packet acknowledgment ratio (PAR), packet delivery ratio (PDR), and Control Message Overhead (CMO), compared to the standard Minimum Rank with Hysteresis Objective Function (MRHOF). 展开更多
关键词 IoT LLNs RPL objective function OF MRHOF OF0 routing metrics reliability trustworthiness
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An Objective Method for Temperature and Wind Forecast at the Venues of the 14 th National Winter Games 认领 引用
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作者 Xuefeng YANG Sitong LIU 《Meteorological and Environmental Research》 2025年第2期59-61,共3页
According to the demand for weather forecast at the venues of the 14 th National Winter Games,based on the data of the fine grid model of the European Centre(EC)and RMAPS model,as well as the real-time observation dat... According to the demand for weather forecast at the venues of the 14 th National Winter Games,based on the data of the fine grid model of the European Centre(EC)and RMAPS model,as well as the real-time observation data of the competition fields,a dynamic optimal correction method was proposed to improve the accuracy rate of temperature and wind speed prediction.Through techniques such as deviation correction and univariate linear regression,mathematical models applicable to different competition regions were constructed,and the effective correction of objective forecast products within 0-120 h were realized.The results show that this method significantly improved the accuracy rate of the prediction of temperature,wind speed and extreme wind speed,and the effect was more obvious especially when the model performance was unstable.Meanwhile,terrain and climate background had a significant impact on the correction effect.This study provides new technical support for mountain meteorological forecast. 展开更多
关键词 Temperature forecast Wind speed forecast Objective correction Dynamic optimum Mountain meteorology
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Correction Algorithm of Temperature Forecast Based on an Objective Optimal Scheme 认领 引用
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作者 Xuefeng YANG Sitong LIU 《Meteorological and Environmental Research》 2025年第2期56-58,共3页
The forecast results of temperature based on the intelligent grids of the Central Meteorological Observatory and the meteorological bureau of the autonomous region and the numerical forecast model of the European Cent... The forecast results of temperature based on the intelligent grids of the Central Meteorological Observatory and the meteorological bureau of the autonomous region and the numerical forecast model of the European Center(EC model)from February to December in 2022 were used.Based on the data of the national intelligent grid forecast,the intelligent grid forecast of the regional bureau,EC model,etc.,temperature was predicted.According to the research of the grid point forecast synthesis algorithm with the highest accuracy rate in the recent three days,the temperature grid point correction was conducted in two forms of stations and grids.In order to reduce the deviation caused by the seasonal system temperature difference,a temperature prediction model was established by using the rolling forecast errors of 5,10,15,20,25 and 30 d as the basis data.The verification and evaluation of objective correction results show that the accuracy rate of temperature forecast by the intelligent grid of the regional bureau,the national intelligent grid,and EC model could be increased by 10%,8%,and 12%,respectively. 展开更多
关键词 Objective correction Optimal extraction Temperature correction Average sliding deviation
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Modeling and multi-objective optimization of a gasoline engine using neural networks and evolutionary algorithms 认领 引用 被引量：9
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作者 JoséD. MARTíNEZ-MORALES Elvia R. PALACIOS-HERNáNDEZ Gerardo A. VELáZQUEZ-CARRILLO 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS CSCD 2013年第9期657-670,共14页
In this paper, a multi-objective particle swarm optimization （MOPSO） algorithm and a nondominated sorting genetic algorithm II （NSGA-II） are used to optimize the operating parameters of a 1.6 L, spark ignition （S... In this paper, a multi-objective particle swarm optimization （MOPSO） algorithm and a nondominated sorting genetic algorithm II （NSGA-II） are used to optimize the operating parameters of a 1.6 L, spark ignition （SI） gasoline engine. The aim of this optimization is to reduce engine emissions in terms of carbon monoxide （CO）, hydrocarbons （HC）, and nitrogen oxides （NOx）, which are the causes of diverse environmental problems such as air pollution and global warming. Stationary engine tests were performed for data generation, covering 60 operating conditions. Artificial neural networks （ANNs） were used to predict exhaust emissions, whose inputs were from six engine operating parameters, and the outputs were three resulting exhaust emissions. The outputs of ANNs were used to evaluate objective functions within the optimization algorithms： NSGA-II and MOPSO. Then a decision-making process was conducted, using a fuzzy method to select a Pareto solution with which the best emission reductions can be achieved. The NSGA-II algorithm achieved reductions of at least 9.84%, 82.44%, and 13.78% for CO, HC, and NOx, respectively. With a MOPSO algorithm the reached reductions were at least 13.68%, 83.80%, and 7.67% for CO, HC, and NOx, respectively. 展开更多
关键词 Engine calibration Multi-objective optimization Neural networks Multiple objective particle swarm optimization（MOPSO） Nondominated sorting genetic algorithm II （NSGA-II）
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Study on the Construction of Whole-course Nursing Objective Management System for Patients with Type 2 Diabetes 认领 引用
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作者 Lei Wu 《Journal of Clinical and Nursing Research》 2025年第1期203-208,共6页
Objective: To explore the effect of a whole-course nursing objective management system on disease control and quality of life in patients with type 2 diabetes, and to propose strategies for constructing such a system ... Objective: To explore the effect of a whole-course nursing objective management system on disease control and quality of life in patients with type 2 diabetes, and to propose strategies for constructing such a system for these patients. Methods: Ninety patients with type 2 diabetes admitted to the Department of Endocrinology of the hospital from January 2024 to June 2024 were selected. The control group (n = 45) received routine nursing care, while the observation group (n = 45) received whole-course nursing. Indicators such as glucose metabolism and compliance behavior were measured before and after care, and the health and quality of life of patients in both groups were evaluated. Results: A comparison of blood glucose levels and compliance behavior showed that the observation group had lower blood glucose levels than the control group (P < 0.05). Additionally, the compliance behavior score of the observation group was higher than that of the control group (P < 0.05). Conclusion: The holistic nursing model demonstrates significant nursing effects for patients with type 2 diabetes. This approach not only assists in blood sugar control, prevents disease progression, and reduces complications, but also enhances patients’ knowledge of health management, aiding in their recovery. 展开更多
关键词 Patients with type 2 diabetes Whole nursing Management system by objectives Construction path
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Closed-loop supply chain network equilibrium strategy model with environmental protection objectives 认领 引用 被引量：2
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作者 Yang Liu Guitao Zhang 《Chinese Journal of Population,Resources and Environment》 2020年第3期251-261,共11页
With the increasing popularity of ecological civilization and sustainable development,enterprises should consider environmental protection measures in their operations in addition to pursue their economic interests.Th... With the increasing popularity of ecological civilization and sustainable development,enterprises should consider environmental protection measures in their operations in addition to pursue their economic interests.This paper establsihes a closed-loop supply chain network model composed of multiple suppliers,manufacturers,retailers,recyclers,and demand markets—regarding their dual goals of the profit maximization and the minimization of carbon emissions.The conditions necessary for establishing overall equilibrium and an equilibrium model of the entire closed-loop supply chain network are determined by applying variational inequality and dual theory.A modified projection contraction algorithm is used to design a model-solving program.Finally,using numerical examples,the paper conducts a comparative static analysis on important parameters such as the weight coefficients of environmental protection objectives and consumers'awareness of low-carbon environmental protection and attains some beneficial enlightenment on management.The results indicate that when the environmental protection objectives of a certain type of enterprise increases,both the economic benefits and environmental protection performance will improve;when the environmental protection objectives of all enterprises increases simultaneously,environmental protection performance improves significantly,but the changes in economic benefits of different enterprises are inconsistent and profit coordination is more complex.Although consumers’awareness of low-carbon preference could improve environmental performance,it reduces the overall profits of network members and the entire closed-loop supply chain network as a whole.The above conclusions can be used as a reference for the government in designing low-carbon environmental protection policy and in closed-loop supply chain research. 展开更多
关键词 Closed-loop supply chain network Environmental protection objectives Nash equilibrium Multi-objective decision-making Environmental protection awareness of consumers
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Multi Objective Decision Making Method Based on Evaluation Criterion for Problems with Linear Value Function 认领 引用
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作者 蒋尚华 韩勇 徐南荣 《Journal of Southeast University(English Edition)》 CAS 1998年第1期114-121,共8页
A class of interactive multi objective decision making method by means of evaluation criterion is proposed for problems with linear value function,in which case,the decision maker(DM) usually has only unwhole informat... A class of interactive multi objective decision making method by means of evaluation criterion is proposed for problems with linear value function,in which case,the decision maker(DM) usually has only unwhole information of weights for objectives. The concept of fault measure of the evaluation criterion is proposed to measure the deviation of the evaluation criterion from the DMs preference structure.The approach to obtain an upper boundary of fault measure of an evaluation criterion,and the approach to modify the evaluation criterion to be one with smaller fault measure,and the approach to obtain a pre optimized objective set by evaluation criterion with certain fault measure are also proposed. 展开更多
关键词 multi objective decision making evaluation criterion fault measure of evaluation criterion pre optimized objective set
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Well production optimization using streamline features-based objective function and Bayesian adaptive direct search algorithm 认领 引用 被引量：10
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作者 Qi-Hong Feng Shan-Shan Li +2 位作者 Xian-Min Zhang Xiao-Fei Gao Ji-Hui Ni 《Petroleum Science》 SCIE CAS CSCD 2022年第6期2879-2894,共16页
Well production optimization is a complex and time-consuming task in the oilfield development.The combination of reservoir numerical simulator with optimization algorithms is usually used to optimize well production.T... Well production optimization is a complex and time-consuming task in the oilfield development.The combination of reservoir numerical simulator with optimization algorithms is usually used to optimize well production.This method spends most of computing time in objective function evaluation by reservoir numerical simulator which limits its optimization efficiency.To improve optimization efficiency,a well production optimization method using streamline features-based objective function and Bayesian adaptive direct search optimization(BADS)algorithm is established.This new objective function,which represents the water flooding potential,is extracted from streamline features.It only needs to call the streamline simulator to run one time step,instead of calling the simulator to calculate the target value at the end of development,which greatly reduces the running time of the simulator.Then the well production optimization model is established and solved by the BADS algorithm.The feasibility of the new objective function and the efficiency of this optimization method are verified by three examples.Results demonstrate that the new objective function is positively correlated with the cumulative oil production.And the BADS algorithm is superior to other common algorithms in convergence speed,solution stability and optimization accuracy.Besides,this method can significantly accelerate the speed of well production optimization process compared with the objective function calculated by other conventional methods.It can provide a more effective basis for determining the optimal well production for actual oilfield development. 展开更多
关键词 Well production Optimization efficiency Streamline simulation Streamline feature Objective function Bayesian adaptive direct search algorithm
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Objective Identification and Climatic Characteristics of Heavy-Precipitation Northeastern China Cold Vortexes 认领 引用 被引量：6
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作者 Xu CHEN Xiaoyong ZHUGE +2 位作者 Xidi ZHANG Yuan WANG Daokai XUE 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2023年第2期305-316,I0009,I0010,共12页
The northeastern China cold vortex(NCCV)plays an important role in regional rainstorms over East Asia.Using the National Centers for Environmental Prediction Final reanalysis dataset and the Global Precipitation Measu... The northeastern China cold vortex(NCCV)plays an important role in regional rainstorms over East Asia.Using the National Centers for Environmental Prediction Final reanalysis dataset and the Global Precipitation Measurement product,an objective algorithm for identifying heavy-precipitation NCCV(HPCV)events was designed,and the climatological features of 164 HPCV events from 2001 to 2019 were investigated.The number of HPCV events showed an upward linear trend,with the highest frequency of occurrence in summer.The most active region of HPCV samples was the Northeast China Plain between 40°–55°N.Most HPCV events lasted 3–5 days and had radii ranging from 250 to 1000 km.The duration of HPCV events with larger sizes was longer.About half of the HPCV events moved into(moved out of)the definition region(35°–60°N,115°–145°E),and half initiated(dissipated)within the region.The initial position was close to the western boundary of the definition region,and the final position was mainly near the eastern boundary.The locations associated with the precipitation were mostly concentrated within 2000 km southeast of the HPCV systems,and they were farther from the center in the cold season than in the warm season. 展开更多
关键词 northeastern China cold vortex heavy precipitation objective identification climatological features
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