Search Results - (( based optimization methods algorithm ) OR ( data deviation based algorithm ))
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Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm
Published 2018“…In this study, a hybrid of the bat algorithm (BA) and the particle swarm optimization (PSO) algorithm, i.e., the hybrid bat-swarm algorithm (HBSA), was developed for the optimal determination of these four parameters. …”
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Logistic regression methods for classification of imbalanced data sets
Published 2012“…Hence, it is required to develop effective imbalanced LR-based methods to be widely used in data mining applications. …”
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Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm
Published 2020“…Data-driven tools are an optimization method to find the optimal controller parameters using the system’s input and output data. …”
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An improved hybrid method combined with a cloud-based supervisory control to facilitate smooth coordination under low-inertia grids
Published 2025“…Furthermore, integrated with IoT-based control, the optimized hybrid generalized droop method mitigates transient instabilities, as evidenced by a 29 % reduction in voltage overshoot during fault clearance. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…The mMVO based method is then used for identifying the parameters of linear and nonlinear subsystems in the Hammerstein model using the given input and output data. …”
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Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending
Published 2006“…To validate the finite element model physical experiments were conducted. A neural network algorithm based on the backpropagation algorithm has been developed. …”
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Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…The K-Means algorithm is the commonest and fast technique in partitional cluster algorithms, although with unnormalized datasets it can achieve local optimal. …”
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem
Published 2021“…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem
Published 2021“…To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model
Published 2023Conference Paper -
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An enhanced sequential exception technique for semantic-based text anomaly detection
Published 2019“…The detection of semantic-based text anomaly is an interesting research area which has gained considerable attention from the data mining community. …”
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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH
Published 2021“…A hybrid population – based stochastic optimization method named MVMO-SH algorithm is proposed to optimize PVDG locations and sizes in the grid system network. …”
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An Empirical Study on the Construction of A Non-Convex Risk Parity Portfolio using a Genetic Algorithm
Published 2025“…Risk-based portfolio optimization has become increasingly crucial due to the limitations and underperformance of traditional Mean-Variance (MV) portfolios. …”
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Estimation of transformers health index based on condition parameter factor and hidden Markov model
Published 2018“…Next, the emission probabilities for each of the condition parameter factors were derived based on frequency of occurrence method. Subsequently, the future states probability distribution was computed based on the HMM prediction model and viterbi algorithm was applied to find the best optimal path sequence of HI for the respective observable condition. …”
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Artificial neural network method modeling of microwave-assisted esterification of PFAD over mesoporous TiO2‒ZnO catalyst
Published 2022“…The evaluation disclosed that the QP algorithm gave the least root mean squared error (RMSE), absolute average deviation (AAD), and the highest determination coefficient (R2) for both training and testing data groups. …”
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Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…The contribution of this work is to optimize the base of Fuzzy membership function of the APFLC by using GA technique. …”
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Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network
Published 2023“…The model reliability describes the second sub-objective, which is to determine the feasible operating window of the MEC using multiple-objective optimization based on the nonlinear convex method using gradient descent algorithm as the objective function in maximizing the percentage efficiency of the MEC after validating the mathematical model. …”
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Comprehensive review of drones collision avoidance schemes: challenges and open issues
Published 2024“…We explore collision avoidance methods for UAVs from various perspectives, categorizing them into four main groups: obstacle detection and avoidance, collision avoidance algorithms, drone swarm, and path optimization. …”
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