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Availability of information in profusion in the internet and databases is common knowledge. It has to be viewed in the backdrop of chances for disclosure of such information by a third party. Privacy Preserving Data Mining (PPDM) is in use for maintaining the privacy of individuals. Numerous updated methods are available for the purpose. Evolutionary Algorithms (EA's) are able to provide effective...
Clustering is an unsupervised technique, which partitions the entire input space into regions. These initial partitions have a great impact on the resulting clusters. In this paper, a new Multi Stage Genetic Clustering (MSGC) scheme for multiobjective optimization in data clustering is proposed, which can automatically partition the data into an appropriate number of clusters. K-means is a well-known...
This article presents a new Unification Matching Scheme (UMS) for information retrieval using the genetic algorithm. The selection of appropriate matching functions contributes to the performance of the information retrieval system. The proposed UMS executes the Unification function on three classical matching functions for different threshold values. The main objective is to utilize all the base...
To address the k shortest paths (KSP) problem, an intelligent optimization approach based on Genetic Algorithm (GA) is presented in this paper. A simple and intuitive natural path representation is firstly employed to be the chromosome encoding scheme. Then genetic operators specific to this encoding scheme are defined respectively. Each partial route of two chosen chromosomes is exchanged by a one-point...
The exiting covariance matching method is not suited for real-time applications due to its demand for exhaustive search. Aiming at this problem, we developed a novel approach based on fuzzy genetic algorithm (GA) to boost the computing efficiency of covariance matching. The approach employs GA in searching for optimal solution in a large image region. To avoid premature convergence or local optimum...
In this paper the design problem of an equi-spaced linear array is considered with the constraint of reducing side lobe level which results in the leakage of the received signal energy. In order to achieve this, powerful tool based on the event of probability has to be chosen. We consider an evolutionary approach, which avoids the adaptive nature and avails the tuning mechanism. Genetic Algorithm...
A search method using an evolutionary algorithm such as a genetic algorithm (GA) is very effective if the parameter is appropriately set. However, the optimum parameter setting was so difficult that each optimal method depending on each problem pattern must be developed one by one. Therefore, this has required special expertise and large amounts of verification experiment. In order to solve this problem,...
Process Industries parameters have to be measured. In Pulp Industry quality of paper (Copier) is determined by many factors of which Brightness and Thickness are the most important. Optimization of parameters is obtained through PSO and results are compared with GA and it is found that PSO has better computational efficiency than GA Effectiveness has increased by using VI as a tool in control process.
This paper presents a new topology optimization method using hybrid genetic algorithm, namely GAOC, using the evolutionary mechanism of the genetic algorithm (GA) and the interpolation scheme of optimality criteria method (OC). In GAOC, the optimality criteria method is used to initialize the genetic population, and GA is then applied to the global search in the fixed design domain. In so doing the...
Ant colony algorithm is a kind of new heuristic biological modeling method which has the ability of parallel processing and global searching. By use of the properties of ant colony algorithm and genetic algorithm, the hybrid algorithm which adopts genetic algorithm to distribute the original pheromone is proposed to solve the continuous optimization problem. Several solutions are obtained using the...
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