Integrative Machine Learning Approaches for Enhanced Real Estate Appraisal: A Multidisciplinary Analysis Incorporating Fuzzy Logic, Aerial Data, and Topographic Information
Abstract: This research paper synthesizes advancements in real estate appraisal by integrating machine learning, fuzzy logic, and aerial data analysis. It critically reviews and analyzes methodologies from recent studies, focusing on their applicability and effectiveness in property valuation. The paper highlights the intersection of these diverse techniques, examining their practical implications in the evolving real estate market. The comprehensive analysis offers insights into the enhanced accuracy and reliability achievable in real estate appraisals through the combined use of data-driven approaches and sophisticated computational methods. This study serves as a significant contribution to the field, providing a detailed evaluation of current practices and their potential in transforming real estate valuation.
Keywords: Aerial Data Analysis, Fuzzy Logic, Machine Learning, Property Valuation, Real Estate Appraisal, Topographic Data
How to Cite?: Abhishek Shende, "Integrative Machine Learning Approaches for Enhanced Real Estate Appraisal: A Multidisciplinary Analysis Incorporating Fuzzy Logic, Aerial Data, and Topographic Information", Volume 10 Issue 9, September 2021, International Journal of Science and Research (IJSR), Pages: 1716-1719, https://www.ijsr.net/getabstract.php?paperid=SR24127215501, DOI: https://dx.doi.org/10.21275/SR24127215501