This paper introduces a new approach of firefly algorithm based on opposition-based learning （OBFA） to enhance the global search ability of the original algorithm. The new algorithm employs opposition based learning...This paper introduces a new approach of firefly algorithm based on opposition-based learning （OBFA） to enhance the global search ability of the original algorithm. The new algorithm employs opposition based learning concept to generate initial population and also updating agents’ positions. The proposed OBFA is applied for minimization of the factor of safety and search for critical failure surface in slope stability analysis. The numerical experiments demonstrate the effectiveness and robustness of the new algorithm.展开更多
Solar energy is a widely used type of renewable energy.Photovoltaic arrays are used to harvest solar energy.The major goal,in harvesting the maximum possible power,is to operate the system at its maximum power point(M...Solar energy is a widely used type of renewable energy.Photovoltaic arrays are used to harvest solar energy.The major goal,in harvesting the maximum possible power,is to operate the system at its maximum power point(MPP).If the irradiation conditions are uniform,the P-V curve of the PV array has only one peak that is called its MPP.But when the irradiation conditions are non-uniform,the P-V curve has multiple peaks.Each peak represents an MPP for a specific irradiation condition.The highest of all the peaks is called Global Maximum Power Point(GMPP).Under uniform irradiation conditions,there is zero or no partial shading.But the changing irradiance causes a shading effect which is called Partial Shading.Many conventional and soft computing techniques have been in use to harvest solar energy.These techniques perform well under uniform and weak shading conditions but fail when shading conditions are strong.In this paper,a new method is proposed which uses Machine Learning based algorithm called Opposition-Based-Learning(OBL)to deal with partial shading conditions.Simulation studies on different cases of partial shading have proven this technique effective in attaining MPP.展开更多
文摘This paper introduces a new approach of firefly algorithm based on opposition-based learning （OBFA） to enhance the global search ability of the original algorithm. The new algorithm employs opposition based learning concept to generate initial population and also updating agents’ positions. The proposed OBFA is applied for minimization of the factor of safety and search for critical failure surface in slope stability analysis. The numerical experiments demonstrate the effectiveness and robustness of the new algorithm.
基金supported by the Xiamen University Malaysia Research Fund XMUMRF Grant No:XMUMRF/2019-C3/IECE/0007(received by R.M.Mehmood)The authors are grateful to the Taif University Researchers Supporting Project Number(TURSP-2020/79),Taif University,Taif,Saudi Arabia for funding this work(received by M.Shorfuzzaman).
文摘Solar energy is a widely used type of renewable energy.Photovoltaic arrays are used to harvest solar energy.The major goal,in harvesting the maximum possible power,is to operate the system at its maximum power point(MPP).If the irradiation conditions are uniform,the P-V curve of the PV array has only one peak that is called its MPP.But when the irradiation conditions are non-uniform,the P-V curve has multiple peaks.Each peak represents an MPP for a specific irradiation condition.The highest of all the peaks is called Global Maximum Power Point(GMPP).Under uniform irradiation conditions,there is zero or no partial shading.But the changing irradiance causes a shading effect which is called Partial Shading.Many conventional and soft computing techniques have been in use to harvest solar energy.These techniques perform well under uniform and weak shading conditions but fail when shading conditions are strong.In this paper,a new method is proposed which uses Machine Learning based algorithm called Opposition-Based-Learning(OBL)to deal with partial shading conditions.Simulation studies on different cases of partial shading have proven this technique effective in attaining MPP.
