Representations of Uncertainty in Artificial Intelligence: Probability and Possibility

International audienceDue to its major focus on knowledge representation and reasoning, artificial intelligence was bound to deal with various frameworks for the handling of uncertainty: probability theory, but more recent approaches as well: possibility theory, evidence theory, and imprecise probabilities. The aim of this chapter is to provide an introductive survey that lays bare specific features of two basic frameworks for representing uncertainty: probability theory and possibility theory, while highlighting the main issues that the task of representing uncertainty is faced with. This purpose also provides the opportunity to position related topics, such as rough sets and fuzzy sets, respectively motivated by the need to account for the granularity of representations as induced by the choice of a language, and the gradual nature of natural language predicates. Moreover, this overview includes concise presentations of yet other theoretical representation frameworks such as formal concept analysis, conditional events and ranking functions, and also possibilistic logic, in connection with the uncertainty frameworks addressed here. The next chapter in this volume is devoted to more complex frameworks: belief functions and imprecise probabilities

Comprehensive overview of optimizing PV-DG allocation in power system and solar energy resource potential assessments

Distributed Generation based on Photovoltaic (PV-DG) injected in the power system is considered a highly promising solution due to the advantage of clean energy use. However, the investigation of the optimal PV-DG allocation (site and size) is a significant task for power system requirements and assessment of PV potentials. Recent research works on PV-DG allocation are reviewed from two viewpoints; (1) DG, optimization algorithms and objectives and (2) methodologies of PV potential assessments. Due to the review of recent research works, the research gaps are identified and new methodology will be proposed. The authors strongly believe that this work can be helpful to mitigate power system challenges. Besides, it helps to maximize the PV harness within the power system in particular developing countries. © 2019 The AuthorsArizona Research Institute for Solar Energy, AzRISEAt the beginning, the author is grateful from YTB (Yurtd??? T?rkler ve Akraba Topluluklar Ba?kanl???) to provide the chance for conducting this study in Turkey. He would also like to thank each of Solar Energy Institute (G?ne? Enerjisi Enstit?s?) in Ege University for providing all necessary needs to complete this work, my supervisor for his tangible guiding and motivating during this academic research and my parents for spiritual support