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Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method
Published 2024“…Genichi Taguchi. In the T-method prediction model, optimization of the model's accuracy is performed through feature selection process by utilizing an orthogonal array. …”
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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm
Published 2025“…After the variable selection process using the proposed method, the optimal prediction model is now formulated with a lesser variable, making it less complex and computationally fast. ? …”
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Optimization of stiffened panel fatigue life by using finite element analysis
Published 2020“…The multi-objective genetic algorithm which selects the design points based on Pareto optimal design combined with the adaptive multi-objective algorithm method which uses an optimal space-filling was shown to be efficient for time limitation and budget. …”
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Optimal loading analysis with penalty factors for generators using brute force method
Published 2022“…This paper reports the optimal loading analysis method using the Brute Force method with and without considering the penalty factor of power line loss. …”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics
Published 2018“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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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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Real-time classification improvement of Indonesian sign system letters (SIBI) using K-Nearest Neighbor algorithm
Published 2024“…A novel approach is introduced to enhance SIBI character predictions using the K-Nearest Neighbor (K-NN) algorithm. …”
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Neural Network Modeling And Optimization For Enzymatic Hydrolysis Of Xylose From Rice Straw
Published 2015“…The process model was developed by the modeling techniques using feed-forward artificial neural network (FANN) and optimized using both particle swarm optimization (PSO) and genetic algorithm (GA). …”
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Bat algorithm and neural network for monthly streamflow prediction
Published 2023“…The applications of artificial intelligence (AI) have been proved to have better performance as compared to conventional statistical method in streamflow prediction. Therefore, this study proposed on the development of streamflow prediction model AI techniques namely Bat algorithm (BA) and backpropagation neural network (BPNN). …”
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Opposition- based simulated kalman filters and their application in system identification
Published 2017“…Metaheuristic optimization algorithms are well-established techniques to address those problems which are difficult to solve through traditional optimization methods. …”
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Hourly yield prediction of a double-slope solar still hybrid with rubber scrapers in low-latitude areas based on the particle swarm optimization technique
Published 2017“…This was achieved by solving an optimization problem using the particle swarm optimization (PSO) algorithm in which the optimal yields were determined by estimating the optimal values of the unknown C and nparameters. …”
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Optimising the production of succinate and lactate in Escherichia coli using a hybrid of artificial bee colony algorithm and minimisation of metabolic adjustment
Published 2015“…This paper proposes a hybrid of the artificial bee colony (ABC) algorithm and the minimisation of metabolic adjustment (MOMA) to predict an optimal set of solutions in order to optimise the production rate of succinate and lactate. …”
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Predictive modeling and optimization of noise emissions in a palm oil methyl ester-fueled diesel engine using response surface methodology and artificial neural network integrated...
Published 2025“…The analysis indicates that the ANN-GA model consistently yields predictions that align more closely with the experimental noise values compared to the RSM model. …”
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Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network
Published 2009“…Experimentally observed responses were used to train, map and optimize the network algorithms before the best architecture was selected. …”
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Artificial intelligence to predict pre-clinical dental student academic performance based on pre-university results: a preliminary study
Published 2024“…Pre-university CGPA was shown to be predictive of dental students’ academic performance; however, alone they did not yield optimal outcomes. …”
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Multi-objectives process optimization in end milling process of aluminium alloy 6061-T6 using genetic algorithm
Published 2024“…For future study, other methods or algorithms can be applied in other machining processes to obtain optimum machining parameters.…”
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Productivity enhancement and modelling of a new double-slope solar still with rubber scrapers in low latitude areas
Published 2018“…Experimental results obtained from the DSSSHS were used to construct the prediction models using the linear regression method and particle swarm optimization (PSO) algorithm with the aid of MATLAB software. …”
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Production and characterization of biochar derived from oil palm wastes, and optimization for zinc adsorption
Published 2015“…The incremental back propagation algorithm demonstrated the best results and which has been used as learning algorithm for ANN in combination with Genetic Algorithm in the optimization. …”
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