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QIMIG:A Quantum-Inspired Evolutionary Framework for Software Library Migration 认领 引用
1
作者 Yun Liu Jinghua Zhao +3 位作者 Liang Ma Zijie Huang Lizhi Cai Jianxin Ge 《Computers, Materials & Continua》 SCIE EI 2026年第9期795-812,共18页
Automated library migration reduces refactoring costs but challenges traditional evolutionary algorithms,which often suffer from premature convergence and poor recall in sparse,complex API mapping spaces.To address th... Automated library migration reduces refactoring costs but challenges traditional evolutionary algorithms,which often suffer from premature convergence and poor recall in sparse,complex API mapping spaces.To address this,we propose QIMIG,a multi-objective optimization framework integrating quantum-inspired encoding with quality-aware and greedy heuristic filtering.QIMIG utilizes a probabilistic Q-bit representation to maintain population diversity and avoid local optima.Simultaneously,its heuristic components leverage historical usage context to filter semantic noise and guide the search toward valid mappings.Evaluated on 9 real-world migration rules derived from 57,447 open-source projects,QIMIG statistically significantly outperforms state-of-the-art baselines such as UNSGA-III.The framework achieves a global mean F1-score of 0.92,exceeding the best-performing baseline by an absolute margin of 0.05,and demonstrates strong stability in resolving complex mapping structures. 展开更多
关键词 Library migration API mapping search-based software engineering quantum-inspired evolutionary algorithm multi-objective optimization
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Android Software Malicious Detection Based on Dynamic Network Traffic Mixing API Information and Feature Importance Analysis 认领 引用
2
作者 Kang Yang Lizhi Cai Jianhua Wu 《Computers, Materials & Continua》 SCIE EI 2026年第7期1882-1899,共18页
Accurate malware identification and family categorization remain significant challenges in large-scale Android software analysis.Although deep learning has surpassed traditional machine learning in performance,its wid... Accurate malware identification and family categorization remain significant challenges in large-scale Android software analysis.Although deep learning has surpassed traditional machine learning in performance,its widespread adoption is hindered by the computational overhead stemming from feature redundancy and the lack of interpretability inherent in its black-box nature.To address these issues,this paper proposes DroidNTA,a DL-based detection model that fuses network traffic and API features.The model first constructs a simplified API Call Graph by extracting the intrinsic structural attributes of applications,and subsequently generates API feature vectors from invocation sequences using a Markov chain algorithm.These are then integrated with dynamic network traffic features to form a final representation vector of the Android instance.To enhance transparency,DroidNTA performs feature contribution analysis by adjusting fusion parameters and employs Shapley values to quantify global feature importance.Experimental results demonstrate that DroidNTA achieves superior performance in both binary and family classification tasks,yielding an accuracy of 99.74%and a gain of over 20%,respectively.We have released our code at http://gffzz188fe103f8f1460as9u5ov6pbuwx969np.ffgz.tsg.suse.edu.cn/joeyyk/DroidNTA. 展开更多
关键词 Android malware deep learning network traffic
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Hybrid Intelligent Approach for the Selection of Third-Party Reverse Logistics Provider under Uncertainty 认领 引用
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作者 宫艳雪 宋俊典 +2 位作者 彭亦功 添玉 郑树泉 《Journal of Donghua University(English Edition)》 EI CAS 2014年第4期484-492,共9页
A hybrid intelligent approach is proposed to help the decision maker to select the appropriate third-party reverse logistics provider. The following process is included: firstly,the evaluation team is established to d... A hybrid intelligent approach is proposed to help the decision maker to select the appropriate third-party reverse logistics provider. The following process is included: firstly,the evaluation team is established to determine the selection criteria and evaluate them by triangular fuzzy numbers; secondly,calculate the weight of criteria by the proposed hybrid algorithm integrating particle swarm optimization( PSO) and simulated annealing( SA); then, the performance evaluation for each supplier is predicted by the proposed self-feedback neural network( SFBNN) based on the historical data. A numerical example is also presented to interpret the methodology above. 展开更多
关键词 hybrid intelligent approach third-party reverse logistics provider uncertainty
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A Service-Oriented Architecture of Cyber-Physical System and Study on Two Key Issues 认领 引用 被引量：1
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作者 王鹏 向阳 张骐 《Journal of Donghua University(English Edition)》 EI CAS 2012年第4期299-304,共6页
As the basis of designing and implementing a cyber-physical system (CPS), architecture research is very important but still at preliminary stage. Since CPS includes physical components, time and space constraints seri... As the basis of designing and implementing a cyber-physical system (CPS), architecture research is very important but still at preliminary stage. Since CPS includes physical components, time and space constraints seriously challenge architecture study. In this paper, a service-oriented architecture of CPS was presented. Further, a two-way time synchronization algorithm for CPS service composition was put forward. And a formal method, for judging if actual CPS service meets space constraints, was suggested, which was based on space-π-calculus proposed. Finally, a case study was performed and CPS business process designed by the model and the proposed methods could run well. The application of research conclusion implies that it has rationality and feasibility. 展开更多
关键词 cyber-physical system (CPS) service-oriented architecture two-way time synchronization space-π-calculus
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Collaborative prediction for bus arrival time based on CPS 认领 引用 被引量：4
5
作者 蔡雪松 《Journal of Central South University》 SCIE EI CAS 2014年第3期1242-1248,共7页
To improve the accuracy of real-time public transport information release system, a collaborative prediction model was proposed based on cyber-physical systems architecture. In the model, the total bus travel time was... To improve the accuracy of real-time public transport information release system, a collaborative prediction model was proposed based on cyber-physical systems architecture. In the model, the total bus travel time was divided into three parts: running time, dwell time and intersection delay time, and the data were divided into three categories of historical data, static data and real-time data. The bus arrival time was obtained by fusion computing the real-time data in perception layer together with historical data and static data in collaborative layer. The validity of the collaborative model was verified by the data of a typical urban bus line in Shanghai, and 1538 sets of data were collected and analyzed from three different perspectives. By comparing the experimental results with the actual results, it is shown that the experimental results are with higher prediction accuracy, and the collaborative prediction model adopted is able to meet the demand for bus arrival prediction. 展开更多
关键词 prediction model cyber-physical system architecture bus arrival time collaborative prediction
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