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An Improved Biogeography-Based Optimization Algorithm for Blocking Flow Shop Scheduling Problem

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Chinese Journal of Electronics 2018年第2期27卷 351-358页

作者： LIU Shufen WANG Pengfei ZHANG Jiachen college of computer science and technology Jilin University

To solve the blocking flow shop scheduling with maximum completion time(i.e. makespan) criterion,we proposed an Improved biogeography-based optimization algorithm(IBBO). The framework of basic BBO algorithm is used in the IBBO algorithm, and the introduction of the NEH algorithm make IBBO algorithm with certain quality and diversity. The migration operation based on the insert rules and the mutation operation based on swap rules are presented to avoid the occurrence of illegal solution of the blocking flow shop problem. An insertneighborhood search algorithm was used to strengthen the local search ability of the IBBO. The computational results show the effectiveness of the proposed IBBO algorithm in solving the blocking flow shop scheduling with maximum completion time criterion.

关键词： Blocking flow shop Biogeography-based optimization Makespan Insert-neighborhood search algorithm

A Hybrid Approach to Maximize Lifetime in Connected Directional Sensor Networks with Adjustable Sensing Ranges

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Chinese Journal of Electronics 2018年第1期27卷 159-167页

作者： LIU Shufen GAO Sihua HAN Lu college of computer science and technology Jilin University

A directional sensor network consists of numerous small sensor nodes that have limited battery power and operate within a restricted sensing range angle. Coverage and connectivity, as two important issues,are widely studied in directional sensor networks. Different from conventional directional sensor nodes in previous studies, those in the present study could adjust their sensing ranges within a range of several values. This paper addresses the Connected adjusted-ranges directional cover(CARDC) problem. The purpose is to organize the directional sensor nodes into a group of connected covers, and assign activities to them, thereby maximizing the network lifetime. We propose a hybrid approach that combines column generation with a genetic algorithm to solve the CARDC problem. The genetic algorithm is utilized to settle the auxiliary problem of column generation, which has the ability to efficiently provide attractive columns for the master problem. Compared with pure integer linear programming formulations, the proposed genetic algorithm significantly improves the speed of column generation method, especially in large-scale networks. The effect variety of number of directions, number of power levels,and communication range on the network lifetime are also investigated.

关键词： Directional sensor networks(DSNs) Coverage and connectivity Column generation Genetic algorithm

Recognizing Social Function of Urban Regions by Using Data of Public Bicycle Systems

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Chinese Journal of Electronics 2019年第1期28卷 13-20页

作者： XU Haitao YING Jing college of computer science and technology Zhejiang University

Obtaining the classification of urban functions is an integral part of urban planning. Currently,public bicycle systems are booming in these years. It conveys human mobility and activity information, which can be closely related to the social function of an urban region. This paper discusses the potential use of public bicycle systems for recognizing the social function of urban regions by using one year’s rent/return data of public bicycles. We found that rent/return dynamics, extracted from public bicycle systems, exhibited clear patterns corresponding to the urban function classes of these regions. With seven features designed to characterize the rent/return pattern, our method based on Smooth support vector machine(SSVM) is proposed to recognize social function classes of urban regions. We evaluate our method based on the large-scale real-world dataset collected from the public bicycle system of Hangzhou. The results show that our method can efficiently recognize different types of urban function areas. Classification results using the proposed SSVM achieved the best classification accuracy of 96.15%.

关键词： Urban regions recognition Public bicycle system Social function classification Smooth support vector machine(SSVM)

Improve the Collaborative Filtering Recommender System Performance by Trust Network Construction

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Chinese Journal of Electronics 2016年第3期25卷 418-423页

作者： DU Yongping DU Xiaoyan HUANG Liang college of computer science Beijing University of Technology

Data sparseness brings significant challenges to the research of recommender systems. It becomes more severe for neighborhood-based collaborative *** introduce the trust relation computing of the sociology field. Instead of the traditional similarity computing method, the trust degree is integrated for the nearest neighbor selection. The trust network is constructed by the expansion of different path length, and the trust value between the users can be obtained by the trust transmission rules. To verify the effectiveness of our method, we give the experiments on different techniques for rating prediction,including Pearson based method, the User position similarity(UPS) based method and the trust with Pearson and UPS. We also give the t-test result. The implementation of the experiment on the Epinions data set shows that the proposed method can improve the system performance significantly.

关键词： Collaborative filtering Trust computing Recommender system

Research on Formal Degree Evaluation and Analysis for Domain Software Based on Evidence

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Chinese Journal of Electronics 2016年第5期25卷 793-800页

作者： BAO Tie LIU Shufen HAN Lu college of computer science and technology Jilin University

Existing researches fail to involve formalized methods in evaluation and analysis of domain software and lack analysis on formal degree, this paper comes up with a formal degree evaluation approach for domain software based on evidence. Various levels of transformation models are mapped by formal analysis of evidence in life cycle of domain software so as to quantitatively measure degree of evidence. Evaluation model based on evidence is established by analyzing detailed evaluation requirement.A level model including mapping condition is established to describe formal degree at hierarchical level. This paper explains detailed evaluation process through an evaluation example. The approach stated in this paper can describe formal degree of domain software, evaluation data can support subsequent bottleneck analysis and trustworthy evolution, thus provide formal support for creditable construction and analysis.

关键词： Software evaluation Domain software Formal degree Evidence metrics

An Optimized Supply Chain Network Model Based on Modified Genetic Algorithm

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Chinese Journal of Electronics 2017年第3期26卷 468-476页

作者： ZHANG Yikun LIU Shufen ZHANG Xinjia college of computer science and technology Jilin University

For complex multi-source,multi-product,multi-stage Supply chain network(SCN)design problem,we propose an optimization supply chain network *** consider cash conversion cycle as an objective to this model and utilize a modified genetic algorithm to solve the *** describe the structure of supply chain network,we propose a new encoding method and a genetic algorithm with modified genetic *** use the Pareto approach to obtain the set of Pareto-optimal *** order to evaluate the performance of the modified genetic algorithm and validate the model,we conduct comparisons with standard genetic algorithm and the simulated annealing genetic *** results show that the modified genetic algorithm achieved better CPU time and the accuracy of the Pareto-optimal solutions than the alternative algorithms and the model was effective.

关键词： Supply chain network(SCN) Genetic algorithm Multi-objective optimization Cash conversion cycle

Quantitative Verification of Knowledge Precondition for Open System

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Chinese Journal of Electronics 2016年第2期25卷 227-233页

作者： XU Weifeng LIU Shufen WANG Xiaoyan college of computer science and technology Jilin University

A quantitative verification method is proposed to quantitatively verify knowledge precondition of actions and plans. Probability epistemic game structure(PEGS) is proposed to model knowledge preconditions in open systems, an extension of concurrent game structure with probabilistic transition. We introduce a probability operator P-λinto Alternating temporal epistemic logic(ATEL) and define a Probability alternating-time temporal epistemic logic(PATEL) for quantitatively model checking the properties of PEGS. We designed an algorithm to compute the probability aiming at model checking verification problems of PATEL based on DTMC and *** convert a portion of the PATEL verification problems into PATL problems by defining the knowledge formulas Ka φ, EA sφ and CA sφ as atomic propositions. We study a train controller using PRISM-games to demonstrate the applicability of above quantitative verification method.

关键词： Quantitative verification Knowledge precondition Alternating-time temporal logic(ATL) Open system

An Automatic Forecasting Method for Time Series

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Chinese Journal of Electronics 2017年第3期26卷 445-452页

作者： LIU Shufen GU Songyuan BAO Tie college of computer science and technology Jilin University

An automatic forecasting method is proposed concerning automation problem in the field of linear time series forecasting. The method is on the basis of econometric theory and overcomes the difficulty to mine and forecast automatically with econometric models. The proposed algorithm is divided into 4 stages, i.e. preprocessing, unit root testing and stationary processing, modeling,and ultimately forecasting. Future values and trends would be estimated and forecasted precisely through the 4 stages of the algorithm according to input data without manual intervention. Experimental comparisons were made between the proposed algorithm and the 2 data driven forecasting algorithms, i.e. moving average method and Holt exponential smoothing method. It was demonstrated with the experimental results that automatic forecasting is feasible utilizing the proposed algorithm and higher accuracy can be acquired than these 2 data driven-based methods.

关键词： Time series Automatic forecasting Unit root test Autoregressive integrated moving average(ARIMA) model

Self-adaptive Processing and Forecasting Algorithm for Univariate Linear Time Series

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Chinese Journal of Electronics 2017年第6期26卷 1147-1153页

作者： LIU Shufen GU Songyuan PENG Jun college of computer science and technology Jilin University

As the Box-Jenkins method could not grasp the non-stationary characteristics of time series exactly, nor identify the optimal forecasting model order quickly and precisely, a self-adaptive processing and forecasting algorithm for univariate linear time series is proposed. A self-adaptive series characteristic test framework which employs varieties of statistic tests is constructed to solve the problem of inaccurate identification and inadequate processing for non-stationary characteristics of time series. To achieve favorable forecasts, an optimal forecasting model building algorithm combined with model filter and candidate model pool is proposed, in which a univariate linear time series forecasting model is built. Experimental data demonstrates that the proposed algorithm outperforms the comparative method in all forecasting performance statistics.

关键词： Time series Self-adaptivity Unit root Autoregressive moving average(ARMA)