基于模糊二型噪声模型的太阳能灌溉系统多目标优化
Multiobjective Optimization of Solar Powered Irrigation System with Fuzzy Type-2 Noise Modelling
摘要：
优化正在成为涉及可持续替代能源系统的工业应用中的关键因素。在这种系统的设计过程中，工程师/决策者在他们的系统与环境相互作用时经常会遇到噪声因素（例如太阳辐射和环境温度波动）。在本章中，考虑了太阳能灌溉系统的尺寸和设计优化。这是一个多变量、噪声、非线性、多目标的问题。这个设计问题的解决，首先使用模糊II型方法来模拟噪声因素。因此，细菌觅食算法（BFA）（在加权和框架的上下文中）被用来解决这个多目标模糊设计问题。然后，该方法被用来构建近似的帕累托前沿，以及在一个模糊的设置，以确定最佳的解决方案。针对所实施的求解方法，对所产生的数值结果进行了全面的分析和讨论。
英文摘要：
Optimization is becoming a crucial element in industrial applications involving sustainable alternative energy systems. During the design of such systems, the engineer/decision maker would often encounter noise factors (e.g. solar insolation and ambient temperature fluctuations) when their system interacts with the environment. In this chapter, the sizing and design optimization of the solar powered irrigation system was considered. This problem is multivariate, noisy, nonlinear and multiobjective. This design problem was tackled by first using the Fuzzy Type II approach to model the noise factors. Consequently, the Bacterial Foraging Algorithm (BFA) (in the context of a weighted sum framework) was employed to solve this multiobjective fuzzy design problem. This method was then used to construct the approximate Pareto frontier as well as to identify the best solution option in a fuzzy setting. Comprehensive analyses and discussions were performed on the generated numerical results with respect to the implemented solution methods.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
