This study discusses the experimental findings on the frequency & temperature influences on the dielectric (constant (ε1) and loss (ε2)) of some chalcogenide materials based on Se83Bi17 composition performed in the temperature range 303 K–393 K and frequency range (100–1000000 Hz). As the frequency increases, multiple polarization mechanisms contribute to the reduction of the dielectric constant. The addition of germanium (Ge) to a composition increases ε1 more than tellurium (Te). The dielectric loss decreases with frequency while increasing with temperature and AC conductivity. Understanding these behaviors is important for material characterization and applications in fields like electronics and solar cells. The theoretical section introduces adaptive neuro-fuzzy inference systems (ANFIS), which are utilized in the estimation of the dielectric characteristics of Se83Bi17 (SB), Se83Bi17Te5 (SB-T), and Se83Bi17Ge5 (SB-G). Experimentation-related data are a source of input. ANFIS model of the Takagi–Sugeno type has been trained. With MATLAB, the most effective networks are created. The outcomes of the ANFIS modeling are exceptional. The accuracy of the modeling process is due to the error values. This study demonstrates that the ANFIS technique can accurately anticipate the dielectric properties of the compositions under consideration when they are formed into thin films. The ANFIS can describe the experimental data of the dielectric (constant (ε1) and loss (ε2)) of some chalcogenide materials for all the mentioned temperatures and frequencies. This leads to using the ANFIS model to produce the dielectric (constant (ε1) and loss (ε2)) of some chalcogenide materials for various temperatures and frequencies which there are no experimental data yet to compare with.
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