Search Results - (( model evaluation method algorithm ) OR ( based application swarm algorithm ))*
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Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost
Published 2024“…PSO-EBGWO is used to optimize the parameters of the CatBoost model. In this method, the Gray Wolf optimized algorithm (EBGWO) is further optimized by particle swarm optimization (PSO), and when combined with it, the convergence performance of the model is improved, the parameters of the model are reduced, and the model is simplified. …”
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Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin
Published 2014“…The algorithm searches the solution space by selecting various model structures and evaluating its fitness. …”
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Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari
Published 2017“…One of the main problems of this method is premature convergence and to improve this problem, the compound of the particle swarm algorithm and genetic algorithm were evaluated. …”
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Hybrid Cat Swarm Optimization and Simulated Annealing for Dynamic Task Scheduling on Cloud Computing Environment
Published 2018“…A multi-objective QoS model based on execution time and execution cost criteria is presented to evaluate the efficiency of the proposed algorithm on CloudSim tool with two different datasets. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…This proposed algorithm is developed based on heuristic method named modified binary particle swarm optimization (MBPSO) with kernel fuzzy clustering method as a fitness function. …”
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Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy
Published 2024“…The HM emerges as a dominant strategy, driven by the Multi-Objective Differential Evolution (MODE) algorithm under literature-based control parameter settings for the mathematical model. …”
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Speed sensorless control of permanent magnet synchronous motor using model reference adaptive system and artificial neural network / Abdul Mu’iz Nazelan
Published 2019“…There are two (2) methods for controlling the PMSM which are sensor-based and sensorless-based methods. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…In the preliminary study, the algorithm is evaluated on the four different peak models of the three EEG signals using the artificial neural network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
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The influence of sentiments in digital currency prediction using hybrid sentiment-based Support Vector Machine with Whale Optimization Algorithm (SVMWOA)
Published 2021“…The proposed Hybrid Sentiment-based Support Vector Machine with a Whale Optimization Algorithm (SVMWOA). will be evaluated and compared based on performance measures. …”
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Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection
Published 2020“…Four state-of-the-art algorithms include particle swarm optimization, flower pollination algorithm, butterfly optimization algorithm, and CBGWO are used to examine the effectiveness of proposed methods in feature selection. …”
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Four Different Methods to Hybrid Simulated Kalman Filter (SKF) with Particle Swarm Optimization (PSO)
Published 2016“…Inspired by the bird flocking, Particle Swarm Optimization (PSO), has been introduced in 1994.Four methods (models) to hybridize SKF and PSO are proposed in this paper. …”
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Conference or Workshop Item -
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Hybrid moth flame optimization mppt algorithm for accurate real-time tracking under partially shaded photovoltaic system
Published 2021“…However, the high computational power of PSO becomes a disadvantage in real-time and highly dynamic MPPT application. In addition, with the continuous improvement effort and the possibility of a new-comer algorithm can show superior results on the current problem, a new MFO based MPPT algorithm was proposed. …”
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Evaluation of lightning return stroke current using measured electromagnetic fields
Published 2012“…On the other hand, indirect methods can evaluate the return stroke current using measured fields and they can cover a greater number of lightning occurrences compared to direct measurement. …”
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Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui
Published 2019“…One of the major research problems is the computation resources required by machine learning algorithm used for classification for HAR. Numerous researchers have tried different methods to enhance the algorithm to improve performance, some of these methods include Support Vector Machine (SVM), Decision Trees, Extreme Learning Machine (ELM), Kernel Extreme Learning Machine (KELM), and Deng’s Reduced Kernel Extreme Learning Machine (RKELM). …”
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Development of soft computing prediction model for the influent physicochemical characteristics of sewage treatment plants / Mozafar Ansari
Published 2021“…In this research, physical and chemical influent characteristics from 2011 to 2013, including flow rate, biochemical oxygen demand (BOD), chemical oxygen demand (COD), Ammoniacal Nitrogen (NH3-N), pH, oil and grease (OG) and suspended solids (SS) of three sewage treatment plants, STP A, STP B, and STP C, in Kuala Lumpur were evaluated. 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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Evaluating JA-ABC5 hyperparameter optimisation with classifiers
Published 2024“…Because of its simplicity, flexibility, and robustness, the Artificial Bee Colony (ABC) algorithm, a swarm intelligence-based optimisation method, has been widely applied in a variety of fields. …”
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