Adaptive slime mould algorithm for optimal design of photovoltaic models

Solar energy is becoming more popular as it a clean source of electricity. The design photovoltaic (PV) cells has therefore captivated experts worldwide. two key issues are the lack an excellent model to define solar and data regarding PV cells. This scenario even impacts module performance (panels). behavior described by current versus voltage. Considering these values, challenge entails solving complicated nonlinear multimodal objectives. Different methods figure out parameters panels have been suggested. They do not come up with best solutions most time. Hence, powerful reliable optimizer needed derive optimal models. To this end, study developed adaptive slime mould algorithm (ASMA) robust precise optimization method. implement ASMA, four improvements proposed: (1) trigonometric-based mutation double-based introduced promote global local search; (2) suitable mechanism adaptively select control SMA; (3) escaping strategy; (4) opposition-based learning operator improve solution. ASMA employed models assessed utilizing total number eight well-known algorithms. findings show that very competitive in terms accuracy convergence speed supported wealth evidence. As result, when assessing model, efficient optimizer. codes proposed will be uploaded for public at http://imanahmadianfar.com http://aliasgharheidari.com.