An Effective Optimization Algorithm for Parameters Identification of Photovoltaic Models

Parameters Identification for Photovoltaic Module Based on an Improved Artificial Fish Swarm Algorithm

A precise mathematical model plays a pivotal role in the simulation, evaluation, and optimization of photovoltaic (PV) power systems. Different from the traditional linear model, the model of PV module has the features of nonlinearity and multiparameters. Since conventional methods are incapable of identifying the parameters of PV module, an excellent optimization algorithm is required. Artific...

Effective and efficient algorithm for multiobjective optimization of hydrologic models

[1] Practical experience with the calibration of hydrologic models suggests that any single-objective function, no matter how carefully chosen, is often inadequate to properly measure all of the characteristics of the observed data deemed to be important. One strategy to circumvent this problem is to define several optimization criteria (objective functions) that measure different (complementar...

An effective optimization algorithm for locally nonconvex Lipschitz functions based on mollifier subgradients

application of the genetic algorithm technique for optimization of the hydrologic tank and simhhyd models’ parameters

in the past decades, much effort has been devoted to simulation of the rainfall-runoff process. hydrological models are simplified representations of the natural hydrologic system. in each case, the choice of the model to be applied depends mainly on the objective of the modeling but also on the available information. the relative performances of two lumped conceptual-based hydrology models (ta...

A Hybrid Optimization Algorithm for Learning Deep Models

Deep learning is one of the subsets of machine learning that is widely used in Artificial Intelligence (AI) field such as natural language processing and machine vision. The learning algorithms require optimization in multiple aspects. Generally, model-based inferences need to solve an optimized problem. In deep learning, the most important problem that can be solved by optimization is neural n...