外文摘要：The techniques for solving complex optimization problems using nature inspired metaheuristic algorithms are widely accepted. Nature inspired methods use nature derived approaches to offer an efficient solution within polynomial time. This paper presents analytics of some of the significant nature inspired metaheuristic algorithms. It elaborates on the principles and concepts that are used in these algorithms representing their similarities, variations, and exceptions. The taxonomical classification and analytics presented in this paper list the nature derived phenomenon used to develop a wide variety of nature-inspired techniques. The algorithms are classified as per the type of agents used, search techniques, sub-optimization methods, type of constraints, and nature of problems. The survey comprehends the use of control parameters like exploration and convergence applicable to these algorithms and their domain specifications. The sources of nature inspiration are also presented with their variants. It establishes the analytics required to choose a specific nature-inspired heuristic algorithm for smart farming and related applications. Metaheuristic algorithms like Particle Swarm optimization, Ant colony optimization, Whale optimization, Firefly optimization, etc. have contributed significantly in assisting smart farming methods for better productivity of crops.
外文关键词：Smart farming;Nature inspired algorithms;Optimization algorithms;Evolutionary algorithms
作者：Mishra, Aishwarya;Goel, Lavika
作者单位：Malaviya Natl Inst Technol Jaipur
期刊名称：IETE TECHNICAL REVIEW
期刊影响因子：0.0
出版年份：2024
出版刊次：41(1)
原文传递申请：江苏省科技资源（工程技术文献）统筹服务平台