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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...
Searching for portfolios co-integrated with an index offers new opportunities in designing robust investment strategies. The problem of finding optimal index co-integrated portfolios that are maximally stationary is combinatorial. Indeed, given a basket of equities, the portfolio/index co-integration cannot be simply expressed in terms of equity/index co-integration. In this paper we investigate the...
Hybrid computational method was used on the basis of available experimental data and production- nutrient ratios were obtained to suggest best nutrient combinations for getting more profitable production of Isabgol. Nutrient combinations could be computed for the choice of farmer. However nutrient combination N 54.435 + P2O5 12.097 + K2O 4.839 Kgha-1 could be detected as best solution for farmers...
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...
Routing and wavelength assignment problem in wavelength division multiplexed optical network is represented as an integer linear program which is found to be NP-complete. Our attention is devoted to such networks operating under wavelength continuity constraint, in which a lightpath must occupy the same wavelength on all the links it traverses. In setting up a lightpath, a route must be selected and...
The task of radar pulse compression is formulated as a multi-objective optimization problem and has been effectively solved using radial basis function (RBF) network and multi-objective genetic algorithm (NSGA-II). The pulse compression performance of three different codes in terms of signal to peak side-lobe ratio (SSR) under noisy environment, range resolution and Doppler shift are evaluated through...
Paper describes a method for finding transmitter parameters (location, power and horizontal direction) for optimal electromagnetic radiation distribution in the observed area. Constraints are protected areas inside the observed area where strength of electric field is limited because of a permanent people presence. In the observed area one wishes to obtain the strength of electric field which is higher...
Machine diagnosis represents fault condition monitoring that may be discrete or continuous and may include preset limit i.e. false alarms, such as green (good), yellow (warning) and red (failure) light indicators to notify low lubrication or low pressure levels. Machine prognosis represents set of activities performed based on diagnostic information to maintain its intended operating condition before...
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...
In this paper, the problem of finding the optimal collision free path, path planning for the case of a controllable mobile robot moving in a static environment filled with obstacles with known shape and size is studied. A path planner based on a hybrid memetic algorithm, genetic artificial immune network (GAIN), which provides near optimal collision free path is proposed. Genetic artificial immune...
The travelling salesman problem (TSP) is one of the extensively studied optimization problem. The numerous direct applications of the TSP bring life to the research area and help to direct future work. To solve this problem many techniques have been developed. Genetic algorithm is one among those which solves this problem by using the processes observed in natural evolution to solve various optimizations...
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...
This paper presents a new algorithm for LDA-based face recognition with selection of optimal principal components using E-coli Bacterial Foraging Strategy (EBFS). A GA-PCA algorithm has been reported to find optimal eigenvalues and corresponding eigenvectors in LDA. In their paper, a fitness function has been proposed to find the optimal eigenvectors to be used in LDA using a Genetic Algorithm (GA)...
The paper introduces a novel three tier architecture to find consensus of Human Papillomavirus (HPV). The proposed procedure is based on simulation and uses all complete genomic DNA sequences of registered HPV strains available in NCBI GenBank. It uses the multiple sequence alignment tool Clustal X to align these sequences. Genetic Algorithm is used to evolve an optimized population of complete genomic...
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...
The paper aims to develop an efficient forecasting model using differential evolution (DE) based learning rule. The structure chosen is an adaptive linear combiner whose weights are trained using DE. The prediction performance of the resulting model is evaluated by feeding features of retail sales data for different months' ahead prediction. These results are compared with those obtained by GA based...
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