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Support Vector Machine (SVM) is a useful technique for data classification with successful applications in different fields of bioinformatics, image segmentation, data mining, etc. A key problem of these methods is how to choose an optimal kernel and how to optimize its parameters in the learning process of SVM. The objective of this study is to propose a Genetic Algorithm approach for parameter optimization...
It is an objective fact that large database has inconsistent data. This paper presents a new rule acquisition method based on rough set theory and genetic algorithm. Using rough set theory, we will divide inconsistent data table into two parts, certain data and possible data, and then standard genetic algorithm is used for mining rules set. When the algorithm is processing, the user is allowed to...
In order to overcome this shortage of general rough set theory, the elementary concept of tolerance rough set theory is proposed, and the theory is employed to build objects' tolerance relations that can correctly classify objects in system. First, we use genetic algorithms to search for the optimal thresholds, then construct special matrix for attributes and objects. Thus we can get the relations...
The cancer classification through gene expression patterns becomes one of the most promising applications of the microarray technology. It is also a significant procedure in bioinformatics. In this study a grid computing based evolutionary mining approach is proposed as discriminant function for gene selection and tumor classification. The proposed approach is based on the grid computing infrastructure...
A robust mixture model-based clustering algorithm using genetic techniques is proposed in this paper. In many engineering and application domains, noisy samples and outliers often exist in data collections, causing negative effects on performance of data mining methods if they are not made aware of these elements. Classical probabilistic mixture-based clustering is one known to be very sensitive to...
Particle Swarm Optimization (PSO) algorithms represent a new approach for optimization. In this paper image enhancement is considered as an optimization problem and PSO is used to solve it. Image enhancement is mainly done by maximizing the information content of the enhanced image with intensity transformation function. In the present work a parameterized transformation function is used, which uses...
This paper proposes to investigate on the efficacy of Genetic Algorithm (GA) based video abstraction system to deliver a meaningful summary (still image abstract) with minimal preprocessing on the given video. The GA employs novel crossover and mutation operators to search for a meaningful summary in a search space of all video summaries. This preliminary investigation employs Euclidean and City-block...
This paper describes GAHWM, a new evolutionary algorithm that integrates genetic algorithm paradigm with an inverted index model to mine the content of HTML documents for effective Web document retrieval. This method is superior in terms of recall and precision over various real life datasets.
The paper presents a QoS multicast routing algorithm based on clonal selection and artificial fish swarm algorithms (CSA-AFSA). The hybrid algorithms reasonably use the superiorities of both algorithms and try to overcome their inherent drawbacks. An improved initialization method is used to make sure each individual in initial population is a reasonable multicast tree without loops. The simulation...
In the last years, the area of Multicriteria Decision Analysis (MCDA) has brought about new methods to cope with classification problems, among which those based on the concept of prototypes. These refer to specific alternatives (samples) of the training dataset that are good representatives of the groups they fit in. In this paper, experiments are conducted over two prototype selection (PS) techniques...
A photomosaic is an image assembled from smaller images called tiles. When a photomosaic is viewed from a distance, it resembles a desired target image. The process of photomosaic generation can be viewed as an optimization problem, where a set of tiles needs to be arranged to resemble a target image. We impose a constraint on the number of times a tile image can be repeated in a photomosaic. A randomized...
Entities of the real world require partition into groups based on even feature of each entity. Clusters are analyzed to make the groups homologous and well separated. Many algorithms have been developed to tackle clustering problems and are very much needed in our application area of gene expression profile analysis in bioinformatics. It is often difficult to group the data in the real world clearly...
Biogeography-Based Optimization (BBO) is a new bio-inspired and population based optimization algorithm. The convergence of original BBO to the optimum value is slow. Intelligent Biogeography-Based Optimization (IBBO) technique is a hybrid version of BBO with Bacterial Foraging algorithm (BFA). In this paper, authors integrate the bacterial intelligence feature of BFA to decide the valid emigration...
Differential evolution (DE) algorithm is a heuristic approach that gains more interest in today's research. It finds the true global minimum regardless of the initial parameter values, fast convergence, and using few control parameters. DE algorithm is a population based algorithm like genetic algorithm using similar operators; crossover, mutation and selection. This paper addresses the restrictive...
BitTorrent has emerged as an effective peer-to-peer application for digital content distribution in the Internet. However, selecting peers in BitTorrent for efficient content distribution still poses a number of challenges due to high heterogeneities of peers with varied rates of uploading bandwidth and dynamic content. This paper presents GA-BT, a genetic algorithm based peer selection optimization...
In this paper we propose an approach for test data generation using genetic algorithm. Our objective is to design a multi-population genetic algorithm using uniform crossover. In this paper we analyze the performance of proposed uniform crossover multi population genetic algorithm method with different combinations of factors that influence the test data generation strategy. For implementing multi-population...
This paper proposes an approach for the design of multiple power system stabilizers (PSS) for multi-area automatic generation control (AGC) system with new deregulated scenario. Here, the concept of DISCO participation matrix (DPM) is also included. The analysis is conducted considering three pre-defined cases, out of which one is the violation of contract case. The optimal parameters of the PSS are...
In many image-processing applications it is necessary to register multiple images of the same scene acquired by different sensors, or images taken by the same sensor but at different times. Mathematical modeling techniques are used to correct the geometric errors like translation, scaling and rotation of the input image to that of the reference image, so that these images can be used in various applications...
Medical image fusion has been used to derive the useful information from multi modal medical images. The proposed methodology introduces evolutionary approaches for robust and automatic extraction of information from different modality images. This evolutionary fusion strategy implements multiresolution decomposition of the input images using wavelet transform. It is because, the analysis of input...
Ant Colony Optimization (ACO) is more suitable for combinatorial optimization problems. This paper proposes Genetic Evolving Ant Colony Optimization (EACO) method for solving unit commitment (UC) problem. The EACO employs Genetic Algorithm (GA) for finding optimal set of ACO parameters, while ACO solves the UC problem. Problem formulation takes into consideration the minimum up and down time constraints,...
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