نتایج جستجو برای: teaching learning based optimization tlbo
تعداد نتایج: 3591766 فیلتر نتایج به سال:
The brushless direct current (BLDC) motor drive is gaining popularity due to its excellent controllability and high efficiency. This paper introduces a fault diagnosis method for open circuit (OC) short (SC) BLDC drives using hybrid classifier with optimization. Features such as current, voltage, speed, torque are considered the training data. features extracted by discrete wavelet transform (D...
This paper presents an improved Teaching Learning Based Optimization (TLO) and a methodology for obtaining the edge maps of the noisy real life digital images. TLO is a population based algorithm that simulates the teaching-learning mechanism in class rooms, comprising two phases of teaching and learning. The 'Teaching Phase' represents learning from the teacher and 'Learning Phase' indicates l...
In this study, a novel effective algorithm called HTC which results from hybridization process between the teaching–learning-based optimization (TLBO) and charged system search (CSS) algorithms is proposed utilized to optimize planar steel frames. Among features of algorithm, simplicity low number setting parameters can be mentioned. The main goals are establish balance exploration exploitation...
previous studies regarding teachers’ beliefs have revealed that teachers’ beliefs have influence on their classroom practices. the current study aimed to investigate the effect of teachers’ beliefs about teaching reading strategies on students’ motivation and success in reading comprehension in the context of english teaching as a foreign language in high schools of mazandaran, iran. data were ...
In the optimum design of reinforced concrete (RC) structural members, robustness employed method is important as well solving optimization problem. some cases where algorithm parameters are defined non-effective values, local-optimum solutions may prevail over existing global results. Any metaheuristic can be effective to solve problem but must give same results for several runs. Due randomizat...
Optimization is the science that presents a solution among available solutions considering an optimization problem’s limitations. algorithms have been introduced as efficient tools for solving problems. These are designed based on various natural phenomena, behavior, lifestyle of living beings, physical laws, rules games, etc. In this paper, new algorithm called good and bad groups-based optimi...
In Smart Grid Demand side management (DSM) plays a crucial role which permits customers to form educated selections concerning their energy consumption. It allows the strength companies lessen height load call for and reshape burden profile. Most of present demand aspect ways utilized in ancient system is with specific techniques algorithms. addition, handle solely restricted range governable l...
Classic unit commitment (UC) is an important and exciting task of distributing generated power among the committed units subject to several constraints over a scheduled time horizon to obtain the minimum generation cost. Large integration of distributed energy resources (DERs) in modern power system makes generation planning more complex. This paper presents the individual and collective impact...
The sine cosine algorithm (SCA) is a recently developed meta-heuristic for solving global optimization problems. It has shown excellent performance in algorithms. But this also shortcomings such as low accuracy, easy to fall into local solution, and slow convergence speed. Aiming at these deficiencies of the SCA, modified with teacher supervision learning (TSL-SCA) proposed. First, strategy can...
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