Search Results - Gravitational research algorithm

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    Performance and Diversity of Gravitational Search Algorithm by Nor Azlina, Ab. Aziz, Marizan, Mubin, Zuwairie, Ibrahim, Sophan Wahyudi, Nawawi

    Published 2014
    “…The findings show that research on improvement of GSA algorithm are needed, specifically in improving the search agents’ diversity. …”
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    An experimental study of modified black hole algorithms by Mohammed, Suad Khairi

    Published 2018
    “…Those algorithms are Black Hole White Hole Algorithm, Gravitational Black Hole Algorithm, Gravitational Black Hole White Hole Algorithm, Black Hole Local Search Algorithm, Black Hole White Hole Local Search Algorithm, Gravitational Black Hole Local Search Algorithm, and Gravitational Black Hole White Hole Local Search Algorithm. …”
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    An Experimental Study of the Application of Gravitational Search Algorithm in Solving Route Optimization Problem for Holes Drilling Process by Omar, Norhaizat, Eng, Chieh Ong, Adam, Asrul, Hasim, Saipol Hadi, Zainal Abidin, Amar Faiz, Jaafar, Hazriq Izzuan, Zakaria, Hamzah, Hassan, Jefery, Nordin, Nur Anis, Osman, Khairuddin, Mohd Hussein, Shamsul Faisal

    Published 2014
    “…The proposed approach involves modeling and simulation of Gravitational Search Algorithm. The performance of the algorithm is benchmark with one case study that had been frequently used by previous researchers. …”
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    A novel solution to traveling salesman problem using fuzzy sets, gravitational search algorithm, and genetic algorithm by Abarghouei, Amir Atapour

    Published 2010
    “…In this approach, suitable fuzzy matrices are used to illustrate the details of the problem. A new optimization algorithm, called the Gravitational Search Algorithm (GSA) is applied to solve TSP as precise as possible, and finally the Genetic Algorithm (GA) finds the final answer in an acceptable amount of time. …”
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    Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri by Mohd Sabri, Norlina

    Published 2020
    “…Based on the capabilities of the metaheuristic algorithms, this research is proposing the enhanced Gravitational Search Algorithm (eGSA) to solve the nano-process parameter optimization problem. …”
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    Improved gravitational search algorithm for optimal placement and sizing of distributed generation for power quality enhancement by Daud, Sa'adah

    Published 2017
    “…In order to obtain the best compromise solution, a novel heuristic algorithm based on improved gravitational search algorithm (IGSA) is proposed as an optimization technique. …”
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    Gravitational Search Algorithm based Long Short-term Memory Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction with Uncertainty by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Tiong S.K., Hossain M.J.

    Published 2024
    “…This paper presents a hybrid approach for predicting the remaining useful life (RUL) and future capacity of lithium-ion batteries (LIBs) using an improved long short-term memory (LSTM) deep neural network with a gravitational search algorithm (GSA). The proposed method address the challenges of nonlinear and dynamic battery behavior, battery aging uncertainty, the requirement for optimal hyperparameters tuning, and the importance of maintaining safe and efficient battery operation. …”
    Conference Paper
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    An adaptive gravitational search algorithm for global optimization by Koay Y.-Y., Tan J.-D., Lim C.-W., Koh S.-P., Tiong S.-K., Ali K.

    Published 2023
    “…In this research, an Adaptive Gravitational Search Algorithm (AGSA) is proposed. …”
    Article
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    Intelligent energy allocation strategy for PHEV charging station using gravitational search algorithm by Rahman, Imran, Vasant, Pandian, Mahinder Singh, Balbir Singh, Abdullah-Al-Wadud, M.

    Published 2014
    “…Higher penetration of PHEVs require adequate charging infrastructure as well as smart charging strategies. We used Gravitational Search Algorithm (GSA) to intelligently allocate energy to the PHEVs considering constraints such as energy price, remaining battery capacity, and remaining charging time.…”
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    Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis by Asrul, Adam

    Published 2018
    “…In this paper, three optimization algorithms which are particle swarm optimization (PSO), gravitational search, and Sine Cosine algorithms are employed to optimize the grinding process parameters that may either reduce the cost, increase the productivity or obtain the finest surface finish and resulting a higher grinding process performance. …”
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    Gravitational Search Algorithm Based LSTM Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction With Uncertainty by Reza M.S., Hannan M.A., Mansor M.B., Ker P.J., Tiong S.K., Hossain M.J.

    Published 2025
    “…This paper presents an improved approach for predicting the RUL and capacity of LIB using a long short-term memory (LSTM) deep neural network-integrated with a gravitational search algorithm (GSA) to address the challenges associated with predicting battery life. …”
    Article
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    Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

    Published 2018
    “…In the OGC framework, the exhibited explorative search behavior of the Gravitational Clustering (GC) algorithm has been addressed by (i) eliminating the agent velocity accumulation, and (ii) integrating an initialization method of agents using variance and median to subrogate the exploration process. …”
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    Classification System for Wood Recognition using K-Nearest Neighbor with Optimized Features from Binary Gravitational Algorithm by Taman, Ishak, Md Rosid, Nur Atika, Karis, Mohd Safirin, Hasim, Saipol Hadi, Zainal Abidin, Amar Faiz, Nordin, Nur Anis, Omar, Norhaizat, Jaafar, Hazriq Izzuan, Ab Ghani, Zailani, Hassan, Jefery

    Published 2014
    “…The project proposes a classification system using Gray Level Co-Occurrence Matrix (GLCM) as feature extractor, K-Nearest Neighbor (K-NN) as classifier and Binary Gravitational Search Algorithm (BGSA) as the optimizer for GLCM’s feature selection and parameters. …”
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