Search Results - (( waste selection method algorithm ) OR ( parameter realization _ algorithm ))
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1
Realization of microcontroller-based polarization control system with genetic algorithm
Published 2009“…To reach optimum performance, the code is optimized by using the best genetic parameter to achieve the fastest execution time. This algorithm consumes low size of memory besides providing fast speed. …”
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2
Parameter-Less Simulated Kalman Filter
Published 2017“…Further studies on the effect of P(0), Q and R values suggest that the SKF algorithm can be realized as a parameter-less algorithm. …”
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3
A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant
Published 2023“…Algorithms; Artificial intelligence; Biochemical oxygen demand; Bioinformatics; Developing countries; Effluent treatment; Effluents; Forecasting; Least squares approximations; Oxygen; Pattern recognition; Support vector machines; Water quality; Biological oxygen demand; Clonal selection algorithms; Least-square support vector machines; Sludge treatment plants; Total suspended solids; Chemical oxygen demand; oxygen; sewage; algorithm; clone; comparative study; effluent; least squares method; nonlinearity; pattern recognition; simulation; sludge; water treatment; activated sludge; algorithm; Article; biochemical oxygen demand; chemical oxygen demand; clonal selection algorithm; comparative study; computer simulation; effluent; forecasting; pattern recognition; prediction; regression analysis; septic sludge treatment plant; sludge treatment; statistical model; support vector machine; suspended particulate matter; waste water treatment plant; chemistry; procedures; sewage; theoretical model; Algorithms; Biological Oxygen Demand Analysis; Forecasting; Least-Squares Analysis; Models, Theoretical; Sewage; Support Vector Machines; Waste Disposal, Fluid…”
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4
LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting
Published 2015“…In this study, a new metaheuristic algorithm, viz., Grey Wolf Optimizer (GWO), is employed to optimize the parameters of interest. …”
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5
Optimization of turning parameters using genetic algorithm method
Published 2008“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). This method was demonstrated for the optimization of machining parameters for turning operation using conventional lathe machines. …”
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Undergraduates Project Papers -
6
Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning
Published 2019“…In contrast, the proposed algorithm realizes a stable computation and reduces the number of parameters compared to existing algorithms. …”
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7
Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction
Published 2014“…The combination of lvABC and cmABC algorithm, which is later introduced as Enhanced Artificial Bee Colony–Least Squares Support Vector Machine (eABC-LSSVM), is realized in prediction of non renewable natural resources commodity price. …”
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8
Rice Predictive Analysis Mechanism Utilizing Grey Wolf Optimizer-Least Squares Support Vector Machines
Published 2015“…In this regard, this study proposes a hybridization of LSSVM with a new Swarm Intelligence (SI) algorithm namely, Grey Wolf Optimizer (GWO). With such hybridization, the hyper-parameters of interest are automatically optimized by the GWO. …”
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Dengue outbreak prediction: hybrid meta-heuristic model
Published 2018“…Here, the FPA is served as an optimization algorithm for LSSVM. The hybrid FPA-LSSVM is later realized for prediction of dengue outbreak in Yogyakarta, Indonesia. …”
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10
Improving PID controller of motor shaft angular position by using genetic algorithm
Published 2015“…This study represents Genetic Algorithm optimization of PID parameters gain in model reference robust control system structure for desired position of incremental servomotor. …”
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Application of LSSVM by ABC in energy commodity price forecasting
Published 2014“…The importance of the hyper parameters selection for a kernel-based algorithm, viz.Least Squares Support Vector Machines (LSSVM) has been a critical concern in literature.In order to meet the requirement, this work utilizes a variant of Artificial Bee Colony (known as mABC) for hyper parameters selection of LSSVM.The mABC contributes in the exploitation process of the artificial bees and is based on Levy mutation.Realized in crude oil price forecasting, the performance of mABC-LSSVM is guided based on Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSPE) and compared against the standard ABC-LSSVM and LSSVM optimized by Genetic Algorithm. …”
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13
Spatial Data Mining Model For Landfill Sites Suitability Mapping Based On Neural Networks And Multivariate Analysis
Published 2017“…Hybrid neural network was utilized as an evaluation method to select the optimal selection method and optimal training algorithm. …”
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14
Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms
Published 2015“…The issues addressed are the sequence of training data for supervised learning and optimum parameter tuning for parameters such as baseline vigilance. …”
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Optimization of process parameters for pyrolsis of waste plastics by T method-1
Published 2023text::Final Year Project -
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Metaheuristic optimization of perovskite solar cell using hybrid L₃₂ Taguchi DoE-based genetic algorithm
Published 2024“…This paper emphasizes the metaheuristic optimization approach in searching for the optimum input parameters of perovskite solar cell (PSC). The proposed approach is realized using Solar Cell Capacitance Simulator (SCAPS-1D) software incorporated with a hybrid L32 Taguchi DoE-based Genetic Algorithm. …”
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Optimisation of laser cutting parameters of oil palm wood / Harizam Mohd Zin
Published 2013“…In some cases, the prediction errors of Taguchi ANN model was found larger than 10% even using a Levenberg Marquardt training algorithm. To overcome the problem, a hybrid genetic algorithm-based Taguchi ANN (GA-Taguchi ANN) has been developed. …”
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18
Development of soft computing prediction model for the influent physicochemical characteristics of sewage treatment plants / Mozafar Ansari
Published 2021“…Sugeno fuzzy inference system (FIS) algorithm was used to model influent parameter, and the FIS parameters were adjusted by ANFIS, integrated Genetic algorithms, GA-FIS, and integrated particle swarm optimisation, PSO-FIS, algorithms. …”
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19
Dynamic smart grid communication parameters based cognitive radio network
Published 2023“…The proposed system helps to drive optimal communication parameters to realize power saving, maximum throughput and minimum bit error rate communication modes. …”
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The effect of key parameters on the design of an optimized CAES power plant
Published 2017“…In order to obtain a more tangible realization, it is necessary to verify the results against the variation of key parameters. …”
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