Search Results - (( using optimization method algorithm ) OR ( features operations using algorithm ))
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Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…In its operation, the metaheuristic algorithm optimizes the feature selection process,which will later be processed using the classification algorithm.Three (3) meta-heuristics were implemented, namely Genetic Algorithm, Particle Swarm Optimization, and Cuckoo Search Algorithm; the experiment was conducted, and the results were collected and analyzed. …”
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An adept edge detection algorithm for human knee osteoarthritis images
Published 2023“…In this paper, Sobel edge detection operator and its enhanced algorithm are first discussed in terms of optimal thresholding in C language under Linux platform. …”
Conference Paper -
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Optimization of Reservoir Operation using New Hybrid Algorithm
Published 2018“…In this research, a new hybrid approach of Artificial Fish Swarm Algorithm (AFSA) and Particle Swarm Optimization Algorithm (PSOA) is used to optimize Karun-4 reservoir, increase energy production and minimize downstream water shortages. …”
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Plant leaf recognition algorithm using ant colony-based feature extraction technique
Published 2013“…Then, based on the characteristics of each species, decision making is done by means of ant colony optimisation as a search algorithm to return the optimal subset of features regarding the related species. …”
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5
Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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6
Crossover and mutation operators of real coded genetic algorithms for global optimization problems
Published 2016“…Second of all, this study operates within experimental design with Taguchi method to discover the optimal design factors for the two proposed genetic operators. …”
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7
Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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8
Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…To achieve this goal, an improved Teaching Learning-Based Optimization (ITLBO) algorithm was proposed in dealing with subset feature selection. …”
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9
New signed-digit {0,1,3}-NAF scalar multiplication algorithm for elliptic curve over binary field
Published 2011“…In conclusion, performance of a scalar multiplication algorithm depends on the digits used in the scalar representation, and the efficiency of the point operations involved in the scalar multiplication algorithm. …”
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10
Improving amphetamine-type stimulants drug classification using chaotic-based time-varying binary whale optimization algorithm
Published 2022“…A new chaotic time-varying binary whale optimization algorithm (CBWOATV) is introduced in this paper to optimize the feature selection process in Amphetamine-type Stimulants (ATS) and non-ATS drugs classification. …”
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11
Development of a new algorithm for segmentation of flotation froth images
Published 2014“…The developed algorithm is validated using some froth images captured at different operating conditions, so the results indicate that the method can segment the mixture of big and small bubbles effectively.…”
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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…The second method is called the Modified Binary Tree Growth Algorithm (MBTGA) that applies swap, crossover, and mutation operators. …”
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14
GA Based Feature Recognition of Step File for CAD/CAM Integration
Published 2009“…A GA model is proposed for optimizing the coordinates which is used for feature recognition. …”
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15
Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
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Depth linear discrimination-oriented feature selection method based on adaptive sine cosine algorithm for software defect prediction
Published 2024“…To address these challenges, this research introduces a novel Depth Linear Discrimination-Oriented Feature Selection Method based on Adaptive Sine Cosine Algorithm, named Depth Adaptive Sine Cosine Feature Selection (DASC-FS). …”
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Efficient classifying and indexing for large iris database based on enhanced clustering method
Published 2018“…The proposed method can be used to perform global search and exhibits quick convergence rate while optimizing the initial clustering centers of the K-means algorithm. …”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei
Published 2020“…In this research, a hybrid electricity price forecasting methodology is proposed using two-stage feature selection method and optimization using adaptive neuro-fuzzy inference system (ANFIS) technique as a forecasting engine. …”
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19
A novel hybrid method of LSSVM-GA with multiple stage optimization for electricity price forecasting
Published 2023Conference Paper -
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Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduct...
Published 2023“…Besides, an optimization algorithm with high efficiency is important to ensure the attainment of optimal solutions, where the optimization algorithms like genetic algorithm and particle swarm optimization are known to have high possibility of being trapped in local optimal points. …”
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