The importance of wireless path loss prediction and interference minimization studies in various environments cannot be over-emphasized. In fact, numerous researchers have done massive work on scrutinizing the effectiveness of existing path loss models for channel modeling. The difficulties experienced by the researchers determining or having the detailed information about the propagating environment prompted for the use of computational intelligence (CI) methods in the prediction of path loss. This paper presents a comprehensive and systematic literature review on the application of nature-inspired computational approaches in radio propagation analysis. In particular, we cover artificial neural networks (ANNs), fuzzy inference systems (FISs), swarm intelligence (SI), and other computational techniques. The main research trends and a general overview of the different research areas, open research issues, and future research directions are also presented in this paper. This review paper will serve as reference material for researchers in the field of channel modeling or radio propagation and in particular for research in path loss prediction.

中文翻译：

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计算智能算法在无线电传播中的应用：系统综述和元数据分析

不能过分强调无线路径损耗预测和最小化干扰研究的重要性。实际上，许多研究人员在审查现有路径损耗模型在通道建模方面的有效性方面已经进行了大量工作。研究人员在确定或掌握有关传播环境的详细信息时遇到的困难促使人们在预测路径损耗时使用了计算智能（CI）方法。本文介绍了关于自然启发式计算方法在无线电传播分析中的应用的全面，系统的文献综述。特别是，我们涵盖了人工神经网络（ANN），模糊推理系统（FIS），群体智能（SI）和其他计算技术。本文还介绍了主要研究趋势以及不同研究领域，开放研究问题和未来研究方向的概述。本文将作为信道建模或无线电传播领域研究人员的参考资料，尤其是路径损耗预测研究的参考资料。