Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-09-12 Cooperative journals: 《计算机应用研究》
Abstract： The reasonable emergency supplies scheduling plays a critical role in emergency rescue. In order to reduce property loss and human casualties, improve the satisfaction of the victims, this paper summarized the supplies scheduling problem under sudden disasters based on bi-level theory and from the perspective of emergency rescue. Focused on the emergency supplies scheduling, it carried out the review and discussion from the perspectives of post-disaster emergency status, emergency material location-allocation, emergency supplies scheduling under different constraints, and the application of bi-level programming and swarm intelligence optimization algorithms in emergency supplies scheduling. The results shows that the research on the post-disaster emergency supplies scheduling currently focuses on the single-level emergency network structure, and the objective function and constraint condition of the model are different from the actual situation. Combining the actual characteristics of the emergency supplies scheduling, this paper proposes some improvement suggestions. It considers the two-level emergency network structure, and then builds a bi-level programming model to achieve joint optimization of the lower and upper level goals.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-08-13 Cooperative journals: 《计算机应用研究》
Abstract： By analyzing the existing cellular automata theory and combining the characteristics of group evacuation, this paper establishes an ordinary supermarket fire evacuation model that considers the attractiveness of exit, fire repulsion, friction, repulsion and occupant psychology. The model fully considers the influence of multiple factors on the evacuation, normalizes the influencing factors, and uses the cell transfer intensity established by considering the comprehensive influencing factors as the pedestrian movement rule. This paper studies the impact of the number of evacuees in supermarket, export width and distance, and herd mentality on evacuation time. Pathfinder+FDS, a simulation evacuation software, is used to verify the model, which showed that the evacuation model has certain credibility. The research shows that pedestrian evacuation time is linearly and positively correlated with the number of evacuees, and there is a critical point for the number of evacuees; the wider the exit width is or the more exits are, the shorter the evacuation time is, but once the exit threshold is reached, the impact on the evacuation time is not significant; in unfamiliar environments or emergency situations, appropriate herding behavior will improve the efficiency of evacuation.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-18 Cooperative journals: 《计算机应用研究》
Abstract： With the green buildings and green-economic environmental cities are gradually formed, "big data green building" energy conservation systems come into being. However, a large number of multi-dimensional building data are not fully utilized and occupancy detection with accuracy of traditional algorithms is not accurate with the higher time complexity. This article acquired the data of Occupancy Detection from UCI. Add a timestamp to the original dataset, the accuracy is increased. Using the MCMR method to select features with maximum correlation and minimum redundancy, random forest is using as classifier to verify classification effect . The XGBoost model constructed by the optimal subset is compared with the random forest model (RF) , and the classification accuracy is higher and the time complexity is lower.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-02 Cooperative journals: 《计算机应用研究》
Abstract： In view of the fact that most phishing websites detection methods have the problems of low detection accuracy and high false positive rate and other issues, this paper proposed a phishing website detection method based on feature selection and integrated learning. Firstly, the FSIGR algorithm was used to select feature. The FSIGR algorithm combined with the advantages of filter and wrapper modes. First, it carried out a comprehensive measurement of features from two aspects of information correlation and classification ability. Second, it used recursive elimination after increasing forward strategy to select the features, and used the classification accuracy as the evaluation index to measure and select the feature subset. Finally, it obtained the optimal feature subset. Then, based on random forest integrated learning classification algorithm, it trained the selected optimal feature subset. Experiments on the UCI dataset show that this method can improve the accuracy of phishing websites detection and reduce the false positive rate.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-04-17 Cooperative journals: 《计算机应用研究》
Abstract： Feature selection is one of the most important issues in data mining, machine learning and pattern recognition. Aiming at the problem of preference of traditional information gain algorithm in feature selection when the class and feature are unevenly distributed, this paper proposes a new feature selection algorithm based on information gain ratio and random forest. The proposed algorithm combined with the advantages of Filter and Wrapper modes. First, a comprehensive measurement of features is carried out from two aspects of information correlation and classification ability. Second, Sequential Forward Selection (SFS) strategy is used to select the features, and the classification accuracy is used as the evaluation index to measure the feature subset. Finally, obtain the optimal feature subset. The experimental results show that the proposed algorithm can not only achieve the effect of dimension reduction in feature space, but also effectively improve the classification performance and recall rate of classification algorithm.
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