Relevant bibliographies by topics / GRAVITATIONAL SEARCH ALGORITHM (GSA)

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'GRAVITATIONAL SEARCH ALGORITHM (GSA)'

Author: Grafiati
Published: 26 October 2023
Last updated: 25 July 2025

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Journal articles on the topic "GRAVITATIONAL SEARCH ALGORITHM (GSA)"

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Lenin, K. "A NOVEL HYBRIDIZED ALGORITHM FOR REDUCTION OF REAL POWER LOSS." International Journal of Research -GRANTHAALAYAH 5, no. 11 (2017): 316–24. http://dx.doi.org/10.29121/granthaalayah.v5.i11.2017.2358.

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This paper proposes Hybridization of Gravitational Search algorithm with Simulated Annealing algorithm (HGS) for solving optimal reactive power problem. Individual position modernize strategy in Gravitational Search Algorithm (GSA) may cause damage to the individual position and also the local search capability of GSA is very weak. The new HGS algorithm introduced the idea of Simulated Annealing (SA) into Gravitational Search Algorithm (GSA), which took the Metropolis-principle-based individual position modernize strategy to perk up the particle moves, & after the operation of gravitation,
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Dr.K.Lenin. "A NOVEL HYBRIDIZED ALGORITHM FOR REDUCTION OF REAL POWER LOSS." International Journal of Research - Granthaalayah 5, no. 11 (2017): 304–12. https://doi.org/10.5281/zenodo.1098401.

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This paper proposes Hybridization of Gravitational Search algorithm with Simulated Annealing algorithm (HGS) for solving optimal reactive power problem. Individual position modernize strategy in Gravitational Search Algorithm (GSA) may cause damage to the individual position and also the local search capability of GSA is very weak. The new HGS algorithm introduced the idea of Simulated Annealing (SA) into Gravitational Search Algorithm (GSA), which took the Metropolis-principle-based individual position modernize strategy to perk up the particle moves, & after the operation of gravitation,
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Lenin, K. "MINIMIZATION OF REAL POWER LOSS BY ENHANCED GRAVITATIONAL SEARCH ALGORITHM." International Journal of Research -GRANTHAALAYAH 5, no. 7 (2017): 623–30. http://dx.doi.org/10.29121/granthaalayah.v5.i7.2017.2171.

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In this paper, Enhanced Gravitational Search (EGS) algorithm is proposed to solve the reactive power problem. Gravitational search algorithm (GSA) results are improved by using artificial bee colony algorithm (ABC). In GSA, solutions are fascinated towards each other by applying gravitational forces, which depending on the masses assigned to the solutions, to each other. The heaviest mass will move slower than other masses and pull others. Due to nature of gravitation, GSA may pass global minimum if some solutions stuck to local minimum. ABC updates the positions of the best solutions that hav
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Dr.K.Lenin. "MINIMIZATION OF REAL POWER LOSS BY ENHANCED GRAVITATIONAL SEARCH ALGORITHM." International Journal of Research - Granthaalayah 5, no. 7 (2017): 523–30. https://doi.org/10.5281/zenodo.844717.

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In this paper, Enhanced Gravitational Search (EGS) algorithm is proposed to solve the reactive power problem. Gravitational search algorithm (GSA) results are improved by using artificial bee colony algorithm (ABC). In GSA, solutions are fascinated towards each other by applying gravitational forces, which depending on the masses assigned to the solutions, to each other. The heaviest mass will move slower than other masses and pull others. Due to nature of gravitation, GSA may pass global minimum if some solutions stuck to local minimum. ABC updates the positions of the best solutions that hav
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Rashedi, Esmat, Hossein Nezamabadi-pour, and Saeid Saryazdi. "GSA: A Gravitational Search Algorithm." Information Sciences 179, no. 13 (2009): 2232–48. http://dx.doi.org/10.1016/j.ins.2009.03.004.

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Shankar, Rajendran, Narayanan Ganesh, Robert Čep, Rama Chandran Narayanan, Subham Pal, and Kanak Kalita. "Hybridized Particle Swarm—Gravitational Search Algorithm for Process Optimization." Processes 10, no. 3 (2022): 616. http://dx.doi.org/10.3390/pr10030616.

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The optimization of industrial processes is a critical task for leveraging profitability and sustainability. To ensure the selection of optimum process parameter levels in any industrial process, numerous metaheuristic algorithms have been proposed so far. However, many algorithms are either computationally too expensive or become trapped in the pit of local optima. To counter these challenges, in this paper, a hybrid metaheuristic called PSO-GSA is employed that works by combining the iterative improvement capability of particle swarm optimization (PSO) and gravitational search algorithm (GSA
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Kamaruzaman, Anis Farhan, Azlan Mohd Zain, Suhaila Mohamed Yusuf, and Noordin Mohd Yusof. "Gravitational Search Algorithm for Engineering: A Review." Applied Mechanics and Materials 815 (November 2015): 417–20. http://dx.doi.org/10.4028/www.scientific.net/amm.815.417.

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This paper presents a review on gravitational search algorithm (GSA). Nowadays, GSA has been used in various engineering studies such as production cost, production time, power consumption and emission. The GSA also mainly focuses to solve the problem related to optimization, modeling, scheduling and clustering. This paper also highlights the current researches using improved GSA.
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Kherabadi, Hossein Azadi, Sepehr Ebrahimi Mood, and Mohammad Masoud Javidi. "Mutation: A New Operator in Gravitational Search Algorithm Using Fuzzy Controller." Cybernetics and Information Technologies 17, no. 1 (2017): 72–86. http://dx.doi.org/10.1515/cait-2017-0006.

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Abstract Gravitational Search Algorithm (GSA) isanovel meta-heuristic algorithm. Despite it has high exploring ability, this algorithm faces premature convergence and gets trapped in some problems, therefore it has difficulty in finding the optimum solution for problems, which is considered as one of the disadvantages of GSA. In this paper, this problem has been solved through definingamutation function which uses fuzzy controller to control mutation parameter. The proposed method has been evaluated on standard benchmark functions including unimodal and multimodal functions; the obtained resul
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Siddique, Nazmul, and Hojjat Adeli. "Gravitational Search Algorithm and Its Variants." International Journal of Pattern Recognition and Artificial Intelligence 30, no. 08 (2016): 1639001. http://dx.doi.org/10.1142/s0218001416390018.

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Gravitational search algorithm (GSA) is a nature-inspired conceptual framework with roots in gravitational kinematics, a branch of physics that models the motion of masses moving under the influence of gravity. In GSA, a collection of objects interacts with each other under the Newtonian gravity and the laws of motion. The performances of objects are measured by masses. All these objects attract each other by the gravity force, while this force causes a global movement of all objects toward the objects with heavier masses. The position of the object corresponds to a solution of the problem. Th
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Ali, Ahmed F., and Mohamed A. Tawhid. "Direct Gravitational Search Algorithm for Global Optimisation Problems." East Asian Journal on Applied Mathematics 6, no. 3 (2016): 290–313. http://dx.doi.org/10.4208/eajam.030915.210416a.

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AbstractA gravitational search algorithm (GSA) is a meta-heuristic development that is modelled on the Newtonian law of gravity and mass interaction. Here we propose a new hybrid algorithm called the Direct Gravitational Search Algorithm (DGSA), which combines a GSA that can perform a wide exploration and deep exploitation with the Nelder-Mead method, as a promising direct method capable of an intensification search. The main drawback of a meta-heuristic algorithm is slow convergence, but in our DGSA the standard GSA is run for a number of iterations before the best solution obtained is passed
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Dissertations / Theses on the topic "GRAVITATIONAL SEARCH ALGORITHM (GSA)"

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KUMAR, NEERAJ. "DESIGNING OF MARKET MODEL, EFFECTIVE PRICE FORECASTING TOOL AND BIDDING STRATEGY FOR INDIAN ELECTRICITY MARKET." Thesis, DELHI TECHNOLOGICAL UNIVERSITY, 2021. http://dspace.dtu.ac.in:8080/jspui/handle/repository/18910.

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The Development scenario for renewable energy across the globe is changing rapidly in terms of capacity addition and grid interconnection. Penetration of renewable energy resources into grid is necessary to meet the elevated demand of electricity. In view of this penetration of solar and wind power growing enormously across the globe. Solar energy is widely escalating in terms of generation and capacity addition due its better predictability over wind energy. Electricity pricing is one of the important aspects for power system planning and it felicitates information for the electricity b
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Drago, Marco. "Search for transient gravitational wave signals with unknown waveform in the LIGO-Virgo network of interferometric detectos using a fully coherent algorithm." Doctoral thesis, Università degli studi di Padova, 2010. http://hdl.handle.net/11577/3422378.

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Gravitational waves are space-time perturbations that are predicted by the General Relativity. Their weak interaction with the matter has neglect a direct detection, however, this has bring to a great effort from the scientific community to construct detectors with high sensitivity and to implement complicated algorithms of signal extraction from noise. For the goal of a detection, the community has realized that the use of more detectors make more realiable on the detection and allows to reconstruct better the waveform characteristics. In this thesis, we have studied a coherent algorithm on
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Grave, Xavier. "Etude de methodes pour la recherche, avec le detecteur virgo d'ondes gravitationnelles emises par des etoiles a neutrons." Paris 11, 1997. http://www.theses.fr/1997PA112105.

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Le but de l'experience virgo est la detection des ondes gravitationnelles. L'objet de cette these est l'etude de methodes pour la recherche de signaux emis par des etoiles a neutrons ainsi que l'etalonnage du detecteur. Dans une premiere partie, l'etoile a neutrons et son emission d'ondes gravitationnelles, sont presentees. Ensuite le detecteur, les principales sources de bruits, ainsi que la solution adoptee pour l'etalonnage sont decrits. Puis dans une seconde partie la modelisation des effets dus aux mouvements de la terre (effet doppler, modulation d'amplitude) est decrite. Leurs consequen
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KUMAR, ARVIND. "FUZZY CLUSTERING FOR COLOR IMAGE SEGMENTATION USING GRAVITATIONAL SEARCH ALGORITHM." Thesis, 2016. http://dspace.dtu.ac.in:8080/jspui/handle/repository/15400.

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Clustering is a key activity in numerous data mining applications such as information retrieval, text mining, image segmentation, etc. This research work proposes a clustering approach, Fuzzy-GSA, based on gravitational search algorithm (GSA). In the proposed Fuzzy-GSA approach, a fuzzy inference system is developed to effectively control the parameters of GSA. The performance of the Fuzzy-GSA algorithm is evaluated against four benchmark datasets from the UC Irvine repository. The results illustrate that the Fuzzy-GSA approach attains the highest quality clustering over the selected dat
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Chien-HungKuo and 郭建宏. "Fuzzy Gravitational Search Algorithm Based Image Zooming Interpolation Scheme." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/34a493.

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碩士<br>國立成功大學<br>電機工程學系<br>103<br>This thesis aims to apply fuzzy gravitation search algorithms to decrease the image zooming inconsistent condition. The image interpolation method distinguishes between the two categories: single frame and multi-frame. The latter is often used in visually, due to the continuous access to live images, so a real-time zooming effect can be achieved. The former is mostly used in repair, reconstruction and local pictures to enlarge the view. In the image scaling process, the hardest part is to increase or maintain the sharpness and smoothness of the image and to red
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Huan-JungChiu and 邱煥榮. "Gait Optimization of Biped Robot Based on Gravitational Search Algorithm." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/07858482778849153385.

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碩士<br>國立成功大學<br>電機工程學系專班<br>101<br>This thesis mainly applies the gravitational search algorithm (GSA) to optimize gait trajectory of a biped robot. In order to reduce the motor assembly costs and allow the motion training to being more convenient, a robotic simulator for biped robots is developed in the thesis, where MATLAB software is adopted. First, the gravitational search algorithm is compared with the particle swarm optimization (PSO) by testing three standard functions to confirm whether it performs better than PSO or not. Then, for a simplified two-dimensional five-link biped robot, th
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Juvvala, Rambabu. "Economic Design of X-bar Control Chart Using Gravitational Search Algorithm." Thesis, 2015. http://ethesis.nitrkl.ac.in/7003/1/Economic_Juvvala_2015.pdf.

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Control chart is a major and one of most widely used statistical process control (SPC) tools. It is used to statistically monitor the process through sampling inspection. Control chart tells us when to allow the process to continue or avoid unnecessary adjustments with machine and when to take the corrective action. On to same problem either on the material side or from the operator side it is quite possible that either targeted value X-bar has changed or process dispersion has changed. These changes must be reflected on the control chart so that the corrective action can be taken. The use of
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Mandal, Abhijeet. "Gravitational Search Algorithm: A Novel Optimization for Economic Design in Discontinuous Model." Thesis, 2015. http://ethesis.nitrkl.ac.in/7812/1/2015_Gravitational_Mandal.pdf.

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Control charts are generally utilized to monitor and maintain the statistical control of a process. Designing a control chart means selection of three parameters such as sample size n, sampling interval h and width of control limits k. To maintain a control chart we have to incur various types of cost such as prevention costs, appraisal costs, internal failure costs, external failure costs and total cost. In economic design the objective is to minimize the total cost associated with control chart. Thus, the economic design is one type of unconstrained optimization problem. Economic designs of
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Tsai, Ming-Yu, and 蔡明佑. "Estimation of Carrier Frequency Offsets for Uplink OFDMA Using Hybrid Particle Swarm Optimization and Gravitational Search Algorithm." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/69y3dw.

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碩士<br>國立臺北科技大學<br>電機工程系研究所<br>100<br>In orthogonal frequency division multiplexing (OFDM) system, carrier frequency offset (CFO) is an important factor that destroys orthogonality among subcarriers. This will lead to inter-carrier interference (ICI) and therefore significantly degrades system performance. Moreover, in the uplink orthogonal frequency division multiple access (OFDMA) system, the base station will receive multiple CFOs from multi-user which causes multiple access interference (MAI), further degrading system performance. Hence the research on CFO estimation has received much atten
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Tsai, Yen-Chuan, and 蔡嬿娟. "Using a revised gravitational search algorithm to find the optimal parameters for a nano-particle milling process." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/96617741639835419431.

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碩士<br>國立雲林科技大學<br>工業工程與管理系<br>102<br>In the early 21st century, the nanotechnology were gradually mature, many industries began using nanotechnology in their product. Thus, nanotechnology becomes an indispensable technology in many industries. In general, many researches commonly used Taguchi methods and algorithms to make the optimal decision. However, there would have errors between actual results and predictions which are calculated by Taguchi method. Therefore, many heuristic algorithms have been developed and used in industry. In all manufacturing process, the producers expect to offer th
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Book chapters on the topic "GRAVITATIONAL SEARCH ALGORITHM (GSA)"

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Kunche, Prajna, and K. V. V. S. Reddy. "Speech Enhancement Approach Based on Gravitational Search Algorithm (GSA)." In Metaheuristic Applications to Speech Enhancement. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31683-3_6.

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González-Álvarez, David L., Miguel A. Vega-Rodríguez, Juan A. Gómez-Pulido, and Juan M. Sánchez-Pérez. "Applying a Multiobjective Gravitational Search Algorithm (MO-GSA) to Discover Motifs." In Advances in Computational Intelligence. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21498-1_47.

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Zhang, Chenglong, Xiaoli Yang, Aizhu Zhang, Dexin Yu, Nian Liu, and Xiaopeng Ma. "GSA-UBS: A Novel Medical Hyperspectral Band Selection Based on Gravitational Search Algorithm." In Advances in Brain Inspired Cognitive Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1417-9_3.

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Lalwani, Praveen, Haider Banka, and Chiranjeev Kumar. "GSA-CHSR: Gravitational Search Algorithm for Cluster Head Selection and Routing in Wireless Sensor Networks." In Applications of Soft Computing for the Web. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-7098-3_13.

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Xing, Bo, and Wen-Jing Gao. "Gravitational Search Algorithm." In Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-03404-1_22.

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Siddique, Nazmul, and Hojjat Adeli. "Gravitational Search Algorithm." In Nature-Inspired Computing. Chapman and Hall/CRC, 2017. http://dx.doi.org/10.1201/9781315118628-2.

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Hashemi, Amin, Mohammad Bagher Dowlatshahi, and Hossein Nezamabadi-Pour. "Gravitational Search Algorithm." In Handbook of AI-based Metaheuristics. CRC Press, 2021. http://dx.doi.org/10.1201/9781003162841-7.

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Zolghadr-Asli, Babak. "Gravitational Search Algorithm." In Computational Intelligence-based Optimization Algorithms. CRC Press, 2023. http://dx.doi.org/10.1201/9781003424765-15.

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Gupta, Aditi, Nirmala Sharma, and Harish Sharma. "Exploitative Gravitational Search Algorithm." In Advances in Intelligent Systems and Computing. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-3322-3_15.

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Rawal, Pragya, Harish Sharma, and Nirmala Sharma. "Fast Convergent Gravitational Search Algorithm." In Algorithms for Intelligent Systems. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-0426-6_1.

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Conference papers on the topic "GRAVITATIONAL SEARCH ALGORITHM (GSA)"

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"A Brief Analysis of Gravitational Search Algorithm (GSA) Publication from 2009 to May 2013." In International Conference Recent treads in Engineering & Technology. International Institute of Engineers, 2014. http://dx.doi.org/10.15242/iie.e0214511.

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Rohmah, Dewi Syifaur, S. Dewi Retno Sari, and K. Vika Yugi. "Clustering human development index data with gravitational search algorithm-fuzzy 4-means (GSA-F4M)." In THE THIRD INTERNATIONAL CONFERENCE ON MATHEMATICS: Education, Theory and Application. AIP Publishing, 2021. http://dx.doi.org/10.1063/5.0039661.

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Pervez, Imran, Adil Sarwar, Mohammad Tayyab, and Mohammad Sarfraz. "Gravitational Search Algorithm (GSA) based Maximum Power Point Tracking in a Solar PV based Generation System." In 2019 Innovations in Power and Advanced Computing Technologies (i-PACT). IEEE, 2019. http://dx.doi.org/10.1109/i-pact44901.2019.8960130.

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Venkat, R., and K. Satyanarayan Reddy. "Dealing Big Data using Fuzzy C-Means (FCM) Clustering and Optimizing with Gravitational Search Algorithm (GSA)." In 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI). IEEE, 2019. http://dx.doi.org/10.1109/icoei.2019.8862673.

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Meziane, Rachid, Seddik Boufala, Amar Hamzi, and Mohamed Amara. "Preventive maintenance optimization in hybrid solar gas power system using gravitational search algorithm." In 2015 3rd International Renewable and Sustainable Energy Conference (IRSEC). IEEE, 2015. http://dx.doi.org/10.1109/irsec.2015.7455130.

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Debnath, Manoj Kumar, Ranjan Kumar Mallick, Sadhana Das, and Aditya Aman. "Gravitational search algorithm (GSA) optimized fuzzy-PID controller design for load frequency control of an interconnected multi-area power system." In 2016 International Conference on Circuit, Power and Computing Technologies (ICCPCT). IEEE, 2016. http://dx.doi.org/10.1109/iccpct.2016.7530205.

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A. Chagas, Elton, Anselmo B. Rodrigues, and Maria G. Silva. "Minimization of Risks of Voltage and Frequency Violations in Islanded Microgrids using Robust Probabilistic Optimal Power Flow." In Simpósio Brasileiro de Sistemas Elétricos - SBSE2020. sbabra, 2020. http://dx.doi.org/10.48011/sbse.v1i1.2386.

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The main aim of this paper is to propose a robust probabilistic optimal power flow model to determine the droop control parameters for the Distributed Generators (DG) of a islanded microgrid. The term robust is related to the droop control parameters being immune to uncertainties associated with: load forecast errors, DG outages and variability of power output in renewable DG. This optimization problem is solved by an improved gravitational search algorithm (GSA). The test results demonstrated that the proposed method can achieve significant reductions in the load curtailments due to frequency
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Katooli, Javad, Mohammad Ameri, and Mohammad Hadi Katooli. "The Application of a Microgrid Considering Wind Generation." In ASME 2015 9th International Conference on Energy Sustainability collocated with the ASME 2015 Power Conference, the ASME 2015 13th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2015 Nuclear Forum. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/es2015-49787.

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Conventional power networks have experienced a gradual evolution from a centralized nature to distributed and localized structures. The upgrading of power system toward a smart grid is being developed to improve reliability and facilitate the integration of different types of renewable energies and improve load management. Due to different uncertainties linked to electricity supply in renewable MGs, probabilistic energy management techniques are going to be necessary to analyze the system. In this study, the short-term operation planning of a typical microgrid (MG) with diverse units for achie
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Saeidi-Khabisi, Fatemeh-sadat, and Esmat Rashedi. "Fuzzy gravitational search algorithm." In 2012 2nd International eConference on Computer and Knowledge Engineering (ICCKE). IEEE, 2012. http://dx.doi.org/10.1109/iccke.2012.6395370.

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Gupta, Aditi, Nirmala Sharma, and Harish Sharma. "Accelerative gravitational search algorithm." In 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, 2016. http://dx.doi.org/10.1109/icacci.2016.7732328.

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