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The following topics are dealt with: intelligent computing and applications; neural network theory and applications; control theory and applications; modeling and simulation; rough set and data mining; intelligent systems; fuzzy systems and applications; factory automation; optimization theory and applications; circuit design and systems; image and signal processing; information security; modeling...
The discrete network design problem deals with the selection of link additions to an existing road network, with given demand from each origin to each destination. The objective is to make an optimal investment decision in order to minimize the total travel cost in the network, while accounting for the route choice behaviors of network users. The discrete network design problem is considered as a...
In view of the coordination difficulty problems existing in relay protection system and high security demand of power supply, the global optimization model for protection settings was set up in power supply network based on the analysis of relay characteristics. A new multi-parameter co-evolutionary genetic algorithm, used to optimize the protection settings, was presented and improved with establishing...
The convergence and local research ability of genetic algorithm is a well concerned research field in recent years. New evolution law of species is introduced in the paper, and based on the new evolution law, compulsive operator was introduced and a new genetic algorithm - compulsive genetic algorithm (CGA) was proposed to improve the convergence of GA. CGA takes advantage of the fitness of current...
AGC unit selection problem has been getting more attention due to economical operation of the power industry. This problem is formulated as a constrained nonlinear mixed integer programming problem with variable unit regulation capacity. Due to the problem including continuous and integral variables, it is difficult to solve the problem using integer programming. PSO has been successfully applied...
This paper presents a new approach via multi-particle swarm optimization (MPSO) to solve the unit commitment (UC) problem. A new strategy which can generate feasible particles and make the search space narrow within the feasible solutions is presented. Some particle swarms are generated by the new strategy, and location optimum solutions are searched in each particle swarm, then a new particle swarm...
Network design problem has originated in the practice of traffic engineering. Planning and designing road system has always been the most important task of traffic engineers. The objective of network design problem is to plan and design an improvement project for a road network systematically so that the total travel cost of the whole road system is minimized. Because of the complexity of the models,...
The model species genomes project has played a very important role in the research of human genomes. By comparing and identifying the genomes' information in the different biological evolution stages with the model species genomes, it is favorable to understand deeply the genomes' structure and function of the advanced species, especially the human being, and to reveal the life's essential law. In...
Image segmentation is a long-term difficult problem, which hasnpsilat been fully solved. Thresholding is one of the most popular algorithms. Particle swarm optimization (PSO) was recently proposed algorithm, which has been successfully applied to solve many optimization problems. Based on the analysis of Otsu threshold selection can be viewed as a continuous optimization problem. Thus, a new method...
Constructing an optimal combinatorial kernel matrix is crucial in kernel methods. We propose a criterion for this model selection problem in the feature space. Differing from the previously popular kernel target alignments criterion, which is subject to limiting the combinatorial matrix that projects the inputs into two additive inverse features, the proposed criterion overcomes the limitation and...
Cluster analysis is an important tool for discovering the structures and patterns hidden in gene expression data. In this paper, a new algorithm for clustering gene expression profiles is proposed. In this method, we find natural clusters in the data based on a competitive learning strategy. Using partially known modes as constraints in our method, we reduce the sensitivity of the clustering procedure...
This paper aims to investigate the internal developing mechanism of a port cluster system. It was proved that a regional port cluster is a typical dissipative structure system, which presents the characteristics of openness, non equilibrium, non linearity and stochastic fluctuation. Considering the port cluster system is a continuous time system, we established the basic evolutionary equations according...
In the environment with partially-known information, the real time path planning can be steadily performed by using the grid method and genetic algorithm; one-dimensional coding problems can be simplified into Two-dimensional path coding problems, at the same time, the obstacle avoidance requirements and shortest paths requirements are integrated into a simple appropriate function. Simultaneously,...
Gene expression programming (GEP) is a new member of evolutionary computation family, and is successful in symbolic regression and function finding in the field of data mining. However, GEP is difficult to find power functions with high ranks. To tackle this problem, this study proposes a novel GEP algorithm named HDN-GEP. The main contributions include: (1) a new structure named HDN (high density...
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