Search Results - (( parameter optimization strategy algorithm ) OR ( changes optimization method algorithm ))

Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi by Dejamkhooy, Abdolmajid, Asefi, Sajjad

“…In the next step, the parameter identification as an optimization problem is solved by Moth-flame optimization, which is a novel nature-inspired heuristic algorithm. …”
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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems by Yasear, Shaymah Akram

“…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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Genetic algorithm tuning based PID Controller for liquid-level tank system by Mohammed Obaid, Ali, S. P., Koh, K. H, Chong, S.K., Tiong, Zeyad Assi, Obaid

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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

“…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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Tree physiology optimization on SISO and MIMO PID control tuning by Halim, A.H., Ismail, I.

“…A simulation of SISO control system and an industrial application of MIMO control are applied to demonstrate the effectiveness of the proposed algorithm and compared with other optimization methods such as particle swarm optimization, Zieglerâ��Nichols, Tyreusâ��Luyben and Chienâ��Hronesâ��Reswick methods. …”
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Tree physiology optimization on SISO and MIMO PID control tuning by Halim, A.H., Ismail, I.

“…A simulation of SISO control system and an industrial application of MIMO control are applied to demonstrate the effectiveness of the proposed algorithm and compared with other optimization methods such as particle swarm optimization, Zieglerâ��Nichols, Tyreusâ��Luyben and Chienâ��Hronesâ��Reswick methods. …”
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Particle Swarm Optimization Of Direct Yaw Control Using Linear Quadratic Integral For Vehicle Stability by Omar, Mohd Firdaus

“…Therefore, in order to achieve an optimum performance of the DYC, the LQI controller gains have been properly selected by using the Particle Swarm Optimization (PSO) algorithm. Apart from optimizing the controller parameters, the LQI with optimization using PSO algorithm capable to maintain the stability of the vehicle in several manoeuvre circumstances. …”
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Short Term Electricity Price Forecasting With Multistage Optimization Technique Of LSSVM-GA by Wan Abdul Razak, Intan Azmira, Zainal Abidin, Izham, Keem Siah, Yap, Zainul Abidin, Aidil Azwin, Abdul Rahman, Titik Khawa

“…Price prediction has now become an important task in the operation of electrical power system.In short term forecast,electricity price can be predicted for an hour-ahead or day-ahead.An hour-ahead prediction offers the market members with the pre-dispatch prices for the next hour.It is useful for an effective bidding strategy where the quantity of bids can be revised or changed prior to the dispatch hour.However,only a few studies have been conducted in the field of hour-ahead forecasting.This is due to most of the power markets apply two-settlement market structure (day-ahead and real time) or standard market design rather than singlesettlement system (real time).Therefore,a multistage optimization for hybrid Least Square Support Vector Machine (LSSVM) and Genetic Algorithm (GA) model is developed in this study to provide an accurate price forecast with optimized parameters and input features.So far,no literature has been found on multistage feature and parameter selections using the methods of LSSVM-GA for hour-ahead price prediction.All the models are examined on the Ontario power market;which is reported as among the most volatile market worldwide.A huge number of features are selected by three stages of optimization to avoid from missing any important features.The developed LSSVM-GA shows higher forecast accuracy with lower complexity than the existing models.…”
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Short term electricity price forecasting with multistage optimization technique of LSSVM-GA by Razak I.A.W.A., Abidin I.Z., Siah Y.K., Abidin A.A.Z., Rahman T.K.A.

“…Therefore, a multistage optimization for hybrid Least Square Support Vector Machine (LSSVM) and Genetic Algorithm (GA) model is developed in this study to provide an accurate price forecast with optimized parameters and input features. …”

Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment by Kalaf, Kalaf, Bayda Atiya

“…On the other hand, consideration of all parameters in an APP model makes the generation of a master production schedule deeply complicated especially in real-world APP problems, where input data or parameters are frequently imprecise (fuzzy) due to incomplete or un obtain able information and daily changes patterns of demand and manufacturers capacity (Sakalhet al., 2010). …”
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Developing NARX Neural Networks for Accurate Water Level Forecasting by Basri H., Razak M.A., Sidek L.M.

“…A nonlinear autoregressive network with exogenous inputs (NARX) model is proposed to predict the water level of the Temengor Reservoir, Perak in Malaysia. The hyper-parameters of the proposed model have been optimized to enhance the accuracy of the proposed model while the Levenberg-Marquardt method was used to train the model. …”

Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

“…In the fast-changing world of digital commerce, predicting online purchasing behavior is essential for improving e-commerce strategies. …”
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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

“…Although useful, strategies based on the aforementioned optimization algorithms are not without limitation. …”
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Advancements in crop water modelling: algorithmic developments and parameter optimization strategies for sustainable agriculture: a review by Sulaiman, Ahmad S. S., Wayayok, Aimrun, Aziz, Samsuzana A., Yun, Wong Mui, Leifeng, Guo

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A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites by Din, Fakhrud

“…Owing to its proven performance in many other optimization problems, the adoption of the parameter-free Teaching Learning-based Optimization (TLBO) algorithm as a new t-way strategy is deemed useful. …”
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Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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Migrating Birds Optimization based Strategies for Pairwise Testing by Hasneeza, L. Zakaria, Kamal Z., Zamli

“…For pairwise testing, test cases are designed to cover all possible pair combinations of input parameter values at least once. In this paper, we investigate the adoption of Migrating Birds Optimization (MBO) algorithm as a strategy to find an optimal solution for pairwise test data reduction. …”
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Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem by Anniza, Hamdan, San Nah, Sze, Say Leng, Goh, Kang Leng, Chiew, Wei King, Tiong

“…Other metaheuristic approaches such as genetic algorithm, differential evolution algorithm, particle swarm optimization, and ant colony optimization are still preferable to address combinatorial optimization problems. …”
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Hybrid Migrating Birds Optimization Strategy for t-way Test Suite Generation by Hasneeza, L. Zakaria, Kamal Z., Zamli, Fakhrud, Din

“…This paper presents the implementation of meta-heuristic search algorithms that are Migrating Birds Optimization (MBO) algorithm and Genetic Algorithm (GA) hybrid to a t-way test data generation strategy. …”
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