Search Results - (( control optimization means algorithm ) OR ( variable optimization based algorithm ))

A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

“…These models are developed by integrating multilayer perceptron neural network and evolutionary optimization techniques. Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

“…Finally, an adaptive neuro-fuzzy inference system (ANFIS) was designed which constructs and optimizes a fuzzy logic controller using a given dataset of input/output variables in order to increase the optimality and stability rates of the proposed path planning algorithm. …”
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Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm by Mohd Riduwan, Ghazali

“…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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Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation by Kamal Z., Zamli, Ahmed, Bestoun S., Mahmoud, Thair, Afzal, Wasif

“…Research has shown that stochastic population-based algorithms such as particle swarm optimization (PSO) can be efficient compared to alternatives for VS-CIT problems. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Evaluation of energy-saving potential for optimal time response of HVAC control system in smart buildings by Homod R.Z., Gaeid K.S., Dawood S.M., Hatami A., Sahari K.S.

Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

Streamflow prediction with large climate indices using several hybrid multilayer perceptrons and copula Bayesian model averaging by Panahi F., Ehteram M., Ahmed A.N., Huang Y.F., Mosavi A., El-Shafie A.

“…Climate models; Flood control; Floods; Forecasting; Information management; Inverse problems; Mean square error; Multilayer neural networks; Multilayers; Normal distribution; Particle swarm optimization (PSO); Reservoir management; Reservoirs (water); Risk management; Rivers; Stream flow; Uncertainty analysis; Bat algorithms; Bayesian model averaging; Bayesian modelling; Copula bayesian model; Gamma test; Inclusive multiple model; Multilayers perceptrons; Multiple-modeling; Natural hazard; Optimization algorithms; Bayesian networks; flood; flood control; North Atlantic Oscillation; perception; reservoir; streamflow; uncertainty analysis; Kelantan; Malaysia; West Malaysia…”

Development Of Two New Auxiliary Information Control Charts, And Economic And Economic-Statistical Designs Of Several Auxiliary Information Control Charts by Ng Peh, Sang

“…The first objective of this thesis is to develop the run sum X - AI (RS X - AI) chart for monitoring the process mean. Optimal parameters computed using the optimization algorithms developed and the step-by-step approach for constructing the optimal RS - AI chart are provided in this thesis. …”
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A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains by Khaksar W., Sahari K.S.M.

“…In this paper, a novel parametric algorithm is proposed that is able to handle different planning goals by means of a set of objective-controller parameters. …”

Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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A proposed variable parameter control chart for monitoring the multivariate coefficient of variation by Chew, X. Y., Khoo, B. C., Khaw, K. W., Yeong, W. C. *, Chong, Z. L.

“…Formulae and algorithms to optimize the various performance measures are discussed. …”
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Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network by Mohamad Afiq, Mohd Asrul

“…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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Modeling and Optimization of Tapered Rectangular Thin-walled Columns Subjected to Oblique Loading for Impact Energy Absorption by Siti Aishah, Rusdan, Tarlochan, Faris, Mohamad Rusydi, Mohamad Yasin

“…The optimal design is obtained by using the constrained nonlinear multivariable optimization algorithm provided by MATLAB. …”
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Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis by Adnani, Seyedeh Atena

“…In this system,similar insolvent system, three methods including one variable at a time, Taguchi method and ANN were used for optimization and prediction of percentage of conversion. …”
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ADAPTIVE MODULATION AND CODING FOR WIMAX SYSTEMS by MAJAVU, WABO

“…First the SNR estimation using the three algorithms is implemented in Wimax system, based on the transmission protocols specified in Wimax. …”
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Applications of Data-driven Models for Daily Discharge Estimation Based on Different Input Combinations by Kumar M., Elbeltagi A., Pande C.B., Ahmed A.N., Chow M.F., Pham Q.B., Kumari A., Kumar D.

Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail by Sh. Ismail, Faridah

“…It optimizes random values for network weights and biases. …”
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Empirical and Neural Network Modelling of Oil Recovery in Nano Assisted Enhanced Oil Recovery by Shafie, A., Irfan, S.A., Aripin, N.

“…The scaled conjugate gradient (SCG) optimization algorithm was used to train the ANN model. …”
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Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals by Paslar, Shahla

“…The idea of hybridizing the newly developed biogeography based optimization algorithm (BBO) with variable neighborhood structure (VNS) is proposed in order to produce a high performance initial schedule in terms of minimum completion time, tardiness and flow time within reasonable amount of time. …”
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