Search Results - (( model validation ((bee algorithm) OR (bat algorithm)) ) OR ( _ information system algorithm ))
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Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions
Published 2018“…Secondly, two meta-heuristics, namely, Bi-Objective Gravitational Search Algorithm (BOGSA) and Bi-Objective Bat Algorithm (BOBAT), were combined to form a (BOGS-BAT) algorithm. …”
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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm
Published 2025“…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. Specifically, a normalization-based Binary Bat algorithm is used, where discretization of continuous solution into binary form is performed using a normalization equation. …”
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Fuzzy Systems and Bat Algorithm for Exergy Modeling in a Gas Turbine Generator
Published 2011“…The fuzzy models are trained applying locally linear model tree algorithm followed by a meta-heuristic nature inspired algorithm called bat algorithm. …”
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A hybrid bat–swarm algorithm for optimizing dam and reservoir operation
Published 2019“…This study proposes a new hybrid optimization algorithm based on a bat algorithm (BA) and particle swarm optimization algorithm (PSOA) called the hybrid bat–swarm algorithm (HB-SA). …”
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Application of augmented bat algorithm with artificial neural network in forecasting river inflow in Malaysia
Published 2024“…Only a few simulation systems, where previous techniques failed to anticipate SF data quickly, let alone cost-effectively, and took a long time to execute. The bat algorithm (BA), a meta-heuristic approach, was used in this study to optimize the weights and biases of the artificial neural network (ANN) model. …”
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New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems
Published 2024“…Thirdly, the thesis validates the algorithm's performance on standard constrained single objective and multi objective benchmark test functions. …”
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Bee colony optimisation of the travelling salesman problem in light rail systems
Published 2019“…The study reported in this paper aimed to identify the most efficient algorithm and develop a mathematical model based on artificial bee colony optimisation to solve this problem in light rail transit systems. …”
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LSSVM parameters tuning with enhanced artificial bee colony
Published 2014“…The proposed model was employed in predicting financial time series data and comparison is made against the standard Artificial Bee Colony (ABC) and Cross Validation (CV) technique.The simulation results assured the accuracy of parameter selection, thus proved the validity in improving the prediction accuracy with acceptable computational time.…”
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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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Transfer learning in near infrared spectroscopy for stingless bee honey quality prediction across different months
Published 2024“…Thus, this study aims to evaluate the feasibility of homogenous transfer learning approaches to overcome data constraints in developing NIRS predictive models of stingless bee honey qualities across different months. …”
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Application of augmented bat algorithm with artificial neural network in forecasting river inflow of hydroelectric reservoir stations in Malaysia
Published 2023“…Uncertainty Analyses such as Taylor Diagram, Violin Plot, Relative Error, and Scatter Plot were applied to further validate the results. The Hybrid BA-ANN model proved to be versatile and robust when being applied to other study areas in Malaysia. …”
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Investigation on the potential to integrate different artificial intelligence models with metaheuristic algorithms for improving river suspended sediment predictions
Published 2023“…Although the adaptive neuro fuzzy system (ANFIS) and multilayer feed-forward neural network (MFNN) have been widely used to simulate hydrological variables, improving the accuracy of the above models is an important issue for hydrologists. In this article, the ANFIS and MFNN models were improved by the bat algorithm (BA) and weed algorithm (WA). …”
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Enhanced ABD-LSSVM for energy fuel price prediction
Published 2013“…This paper presents an enhanced Artificial Bee Colony (eABC)based on Lévy Probability Distribution (LPD) and conventional mutation. …”
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Analysis the effectiveness of cryogenic treatment through roughness and temperature prediction using bonn technique / Manjunath.S and Ajay Kumar
Published 2017“…Thus, the bat algorithm coupled with artificial neural network is a dynamic and specific method in advancing the overall least possible method for surface roughness prediction in face milling operations.…”
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Optimizing Visual Surveillance Sensor Coverage Using Dynamic Programming
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Enhanced ABC-LSSVM For Energy Fuel Price Prediction
Published 2014“…To evaluate the effi ciency of the proposed model, crude oil prices data was employed as empirical data and a comparison against four approaches were conducted, which include standard ABC-LSSVM, Genetic Algorithm-LSSVM (GA-LSSVM), Cross Validation-LSSVM (CV-LSSVM), and conventional Back Propagation Neural Network (BPNN). …”
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Modified anfis architecture with less computational complexities for classification problems
Published 2018“…The proposed ANFIS model is trained by one of the metaheuristics approach instead of standard two pass learning algorithm. …”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…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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