Titlebook: Intelligent Data Engineering and Automated Learning – IDEAL 2016; 17th International C Hujun Yin,Yang Gao,Antonio J. Tallón-Ballesteros Con

折磨

From Parzen Window Estimation to Feature Extraction: A New Perspective,nd attempt to extract fewer features from the original data space according to a certain criterion. The other originates from dimension reduction deviation and tries to make the deviation between data before and after dimension reduction be as small as possible. However, there exists almost no any s

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單色

Enhancing State Space Search for Planning by Monte-Carlo Random Walk Exploration,determines the search efficiency. In state space search for planning, a well-observed phenomenon is that for most of the time during search, it explores a large number of states while the minimal heuristic value has not been reduced. This so called “plateau escape” phenomenon has attracted many inte

Antecedent

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An Effective Genetic Algorithm with Uniform Crossover for Bi-objective Unconstrained Binary Quadrater, we propose an effective multi-objective genetic algorithm with uniform crossover for solving bi-objective unconstrained binary quadratic programming problem. In this algorithm, we integrate the uniform crossover within the hypervolume-based multi-objective optimization framework for further impr

wangle

MONY

A Note on the ,-NN Density Estimate,problem of .-NN approach has been intensively investigated. In particular, the equivalence of convergence in weak or strong sense (i.e. in probability sense or in almost surely sense) has been respectively developed. In this note, we will show that the .-NN estimator converges in probability is equi

灌輸

Visualizing MOOC User Behaviors: A Case Study on XuetangX,rse. However, despite of the encouraging performance achieved, the dataset itself is largely not well investigated. To gain an in-depth understanding of MOOC user behaviors, we conduct two case studies on the dataset containing the information of 79,186 users and 39 courses. In the first case study,

惡心

Modified-DBSCAN Clustering for Identifying Traffic Accident Prone Locations,raffic accident prone locations is in urgent need. This work proposes a modification of DBSCAN clustering algorithm with parameters . and . carefully chosen for identifying traffic accident prone locations. Experimental results on traffic accident datasets of three national expressways are given, de

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