Titlebook: Applied Computing; Second Asian Applied Suresh Manandhar,Jim Austin,Asoke K. Talukder Conference proceedings 2004 Springer-Verlag Berlin He

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Contributions to Management Sciencek criterion, i.e. F2|d.= d|Y., which is known to be NP-hard. In computational experiments, we compared the practical efficiency of a dynamic programming approach, an enumerative method and heuristic procedures. Test results showed that each solution method has its advantages and it cannot be rejected from the consideration a priori.

DRAFT

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Lecture Notes in Computer Sciencelation of multimodal optimization into a multiobjective framework. For both multimodal and multiobjective problems, most implementations need niching/sharing to promote diversity in order to obtain multiple (near-) optimal solutions. Such techniques work best when one has . knowledge of the problem

Rustproof

Engineering Interactive Systems 2008is embedded to initiate the Kohonen classifers. By the proposed approach, the neural network learning performance and accuracy are greatly enhanced. In addition, the genetic algorithm can successfully avoid the neural network from being trapped in a local minimum. The proposed method was tested for

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Engineering Interrelated Electricity Marketsle model (IMM) filtering has been used for tracking multiple targets successfully. IMM needs to evaluate model probability using an observation assigned to the track. We propose a tracking algorithm based on IMM which exploits the genetic algorithm for data association. Genetic algorithm performs ne

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Engineering Interrelated Electricity Marketsac measurements in postero-anterior (PA) and lateral view of chest radiograph Determination of heart size is a major factor in the clinical evaluation of the healthy or failing heart. In this paper, we describe an automatic method for computing the approximate volume of the heart based on cardiac re

Connotation

The Electricity Sector Simulation Modeleveloped to solve it. In this paper, a complementary problem for the original problem is defined. Due to the structure of the feasible domain and nature of the objective function, individual variable is restricted to become bi-valued. We propose a procedure for separating the decision variables into

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Contributions to Management Sciencet. In a classification model, the connection between classes and properties can be defined by something as simple as a flowchart or as complex and unstructured as a procedures manual. Classifier committee learning methods generate multiple classifiers to form a committee by repeated application of a

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