Search Results - (( based optimization method algorithm ) OR ( data application new algorithm ))
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…GA is a widely used optimization algorithm based on the concept of survival of the fittest. …”
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2
Optimizing lossless compression by normalized data length in Huffman Algorithm
Published 2022“…The proposed new algorithm has more optimal CR than the various variants of the Huffman-based lossless application. …”
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Data clustering using the bees algorithm
Published 2007“…The authors’ team have developed a new population based search algorithm called the Bees Algorithm that is capable of locating near optimal solutions efficiently. …”
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Algorithm development for optimization of a refrigeration system
Published 2010“…The thesis describes the step by step the method to find an algorithm by using experimental data. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…In this study we show how to apply a particular class of optimization methods known as pattern search methods to address these challenges. …”
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New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems
Published 2024“…The increasing interest among researchers in the application of metaheuristic algorithms for search optimization has resulted in notable progress, especially in tackling single objective optimization problems. …”
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7
Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering
Published 2024“…To address the noise problem in multi-view data, this study enhances the gbs method and develops a new self-weighted graph multi-view clustering algorithm (swmcan). …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…This strategy includes a number of components that are a novel approach to clustering generation. In fact a data clustering method is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on our proposed algorithm; which is Enhanced Binary Particle swarm Optimization (EBPSO), (ii) To mine data using various data chunks (windows) and overcome a failure of single clustering. …”
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Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system
Published 2018“…In addition, it is expected that it can be applied in real-time application. In this study, Simulated Kalman Filter (SKF) is applied to image template matching application as the optimization algorithm. …”
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10
Intelligent web proxy cache replacement algorithm based on adaptive weight ranking policy via dynamic aging
Published 2016“…However, their performances are not well optimized. This work proposes a hybrid method that optimize cache replacement algorithm using Naïve Bayes (NB) based approach. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The new proposed method (MBPSO+MKN+GK) Gustafson- Kessel algorithm (GK)integrated with modified of Kohonen Network algorithm (MKN)and modified binary particle swarm optimization (MBPSO) was used to classify the credit scoring data. …”
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12
A new ant based rule extraction algorithm for web classification
Published 2011“…Web documents contain enormous number of attributes as compared to other type of data. Ant-Miner algorithm is also still lacking in efficiency, accuracy and rule simplicity because of the local minima problem.Therefore, the Ant-Miner algorithm needs to be improved by taking into consideration of the accuracy and rule simplicity criteria so that it could be used to classify Web documents data sets or any large data sets.The best attribute selection method for Web texts categorization is the combination of correlation-based evaluation with random search as the search method.However, this attribute selection method will not give the best performance in attributes reduction. …”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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14
Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection
Published 2020“…Four state-of-the-art algorithms include particle swarm optimization, flower pollination algorithm, butterfly optimization algorithm, and CBGWO are used to examine the effectiveness of proposed methods in feature selection. …”
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A harmony search algorithm for university course timetabli
Published 2012“…The major thrust of this algorithm lies in its ability to integrate the key components of population-based methods and local search-based methods in a simple optimization model. …”
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A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network
Published 2023“…Compared to the Ant Colony Optimization-Genetic Algorithm (ACO-GA) and Ant Colony Optimization- Hierarchical Clustering Mechanism (ACOHCM), the ACO algorithm shows superior power savings and efficiency. …”
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18
Integrating genetic algorithms and fuzzy c-means for anomaly detection
Published 2005“…In this paper we propose an intrusion detection method that combines Fuzzy Clustering and Genetic Algorithms. …”
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Conference or Workshop Item -
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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20
A review on the applications of PSO-based algorithm in demand side management: Challenges and opportunities
Published 2023“…The implementation of Artificial Intelligence algorithms in DSM applications has been employed in many studies to help researchers make optimal decisions and achieve predictions by analyzing the massive amount of historical data. …”
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