Fuzzy Decision Algorithm for Health Impact Assessment in a 5G Environment

Abstract

The widespread use of mobile phones and other wireless communication devices raises concerns about radiation’s impact on humans. A new algorithm for making decisions for the assessment of the biological impact of non-ionizing radiation is presented in this paper. The algorithm was developed according to ICNIRP (the International Commission on Non-Ionizing Radiation Protection) guidelines using fuzzy logic. Appropriate membership function choices and optimized fuzzy rule selections are crucial for fuzzy modeling. Fuzzy logic is widely applied for multiparameter process modeling using linguistic forms and mathematical expressions. A comprehensive analysis of 4G and 5G network parameters was carried out including electrical and magnetic field strengths, frequency ranges, power densities, and exposure times. The proposed hands-on fuzzy decision-making algorithm can be used for fast, easy, and reliable non-ionizing radiation risk assessment for the following social groups: residents, on-site workers, and professional users.

Fuzzy Set and Soft Set Theories as Tools for Vocal Risk Diagnosis

“…Fuzzy set theory has been studied extensively over the past 50 years and has been applied to problems in engineering, business, agriculture, medicine, and other related felds. Recently, fuzzy techniques have been used to design a sustainable development model for the agricultural sector for the critical circumstances of the COVID-19 pandemic [4], to assess the strength of competition among competitors in the feld of competitive network system [5], to present a novel rule-based approach using picture fuzzy sets to enable intelligent clinical decision support system [6], to propose a complete system for managing and extracting information in health systems using big data architecture [7], to present a new algorithm for making decisions for the assessment of the biological impact of nonionizing radiation [8], and to develop the rough D-TOPSIS method which provides a more comprehensive and rational framework for evaluation of crops farming without any assumptions or predetermined membership functions and which is applied in agricultural farming for increasing crop production in a specifc region with certain soil characteristics and water requirements and investment analysis in organic and inorganic farming systems [9] and to propose a novel model called dual 2-tuple linguistic rough number (D2tLRN) clouds or dual 2-tuple linguistic rough integrated (D2tLRN) clouds which is integrated with the TOPSIS method for the selection of medical disposal technologies [10]. Also, using the concepts of fuzzy set theory, some extensions have been proposed, such as an innovative concept of extended fuzzy set, in which the S-norm function of membership and nonmembership grades is less than or equal to one [11], a defnition of bipolar gradation of openness of bipolar fuzzy subsets and give a new defnition of bipolar fuzzy topological spaces [12], a new type of generalized fuzzy sets called CR-fuzzy sets [13], a novel concept called a linguistic complex fuzzy set [14], a new linguistic evaluation model they called the fuzzy integrated clouds (RFIC), to handle uncertain information by integrating approximate fuzzy numbers with cloud model theory [15], among others that have recently appeared.…”