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A non-dominated sorting Differential Search Algorithm Flux Balance Analysis (ndsDSAFBA) for in silico multiobjective optimization in identifying reactions knockout
Published 2019“…The proposed ndsDSAFBA method was validated using three genome-scale metabolic models. …”
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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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Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm
Published 2025“…Complementing this, the Harmony Search Algorithm (HSA) is incorporated to augment data features, facilitating better pattern recognition and enhancing overall classification accuracy through optimized feature engineering. …”
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A non-dominated sorting differential search algorithm flux balance analysis (ndsDSAFBA) for in silico multiobjective optimization in identifying reactions knockout
Published 2019“…The proposed ndsDSAFBA method was validated using three genome-scale metabolic models. …”
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CUCKOO SEARCH OPTIMIZATION NEURAL NETWORK MODELS FOR FORECASTING LONG-TERM PRECIPITATION
Published 2024“…This paper presents the application of a novel optimization algorithm, Cuckoo Search Optimization (CSO), to train feedforward neural networks to forecast long-term precipitation using three climate models, namely HadCM3, ECHAM5, and HadGEM3‐RA. …”
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Book Chapter -
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Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization
Published 2022“…Integration of global search algorithm into ANN model further improved the model performance. …”
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Thesis -
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Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain
Published 2014“…Finally to present the model validity of a real case study in automotive industrial was studied. …”
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Composite nonlinear feedback control with multi-objective particle swarm optimization for active front steering system
Published 2024journal::journal article -
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Metaheuristic techniques in enhancing the efficiency and performance of thermo-electric cooling devices
Published 2017“…The objective of this paper is to focus on the technical issues of single-stage thermo-electric coolers (TECs) and two-stage TECs and then apply new methods in optimizing the dimensions of TECs. In detail, some metaheuristics-simulated annealing (SA) and differential evolution (DE)-are applied to search the optimal design parameters of both types of TEC, which yielded cooling rates and coefficients of performance (COPs) individually and simultaneously. …”
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Solving vehicle routing problem by using improved K-nearest neighbor algorithm for best solution
Published 2017“…Objectives: Our paper attempt to find an optimal route result for VRP by using K-Nearest Neighbor Algorithm (KNNA). …”
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Intelligent approach for process modelling and optimization on electrical discharge machining of polycrystalline diamond
Published 2018“…Response surface plot was drawn to study the influences of machining parameters of EDM for shaping PCD with copper tungsten and copper nickel. Subsequently, moth search algorithm (MSA) was used to determine the optimal machining parameters, such that the MRR was maximized and EWR was minimized. …”
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Intelligent approach for processmodelling and optimization on electrical dischargemachining of polycrystalline diamond
Published 2020“…Response surface plot was drawn to study the influences of machining parameters of EDM for shaping PCD with copper tungsten and copper nickel. Subsequently, moth search algorithm (MSA) was used to determine the optimal machining parameters, such that the MRR was maximized and EWR was minimized. …”
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Severity prediction of traffic accidents with recurrent neural networks
Published 2017“…Further, the network was trained with a Stochastic Gradient Descent (SGD) algorithm (learning rate = 0.01) in the Tensorflow framework. …”
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Severity prediction of traffic accidents with recurrent neural networks
Published 2017“…Further, the network was trained with a Stochastic Gradient Descent (SGD) algorithm (learning rate = 0.01) in the Tensorflow framework. …”
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Enhancing three variants of harmony search algorithm for continuous optimization problems
Published 2021“…Meta-heuristic algorithms are well-known optimization methods, for solving real-world optimization problems. …”
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A modified crow search algorithm with niching technique for numerical optimization
Published 2019“…Despite its easy implementation, crow search algorithm has weakness to find global optima and suffers from slow convergence rate in multi-modal optimization problems. …”
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Conference or Workshop Item -
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A modified crow search algorithm with niching technique for numerical optimization
Published 2019“…Despite its easy implementation, crow search algorithm has weakness to find global optima and suffers from slow convergence rate in multi-modal optimization problems. …”
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Conference or Workshop Item -
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Hospital site suitability assessment using three machine learning approaches: evidence from the Gaza strip in Palestine
Published 2021“…Identification of the most significant parameters (conditioning factors) that influence a suitable hospital location was achieved by employing correlation-based feature selection (CFS) with the search algorithm (greedy stepwise). Thus, the suitability map of potential hospital sites was modeled using a support vector machine (SVM), multilayer perceptron (MLP), and linear regression (LR) models. …”
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