Explainable Artificial Intelligence Based On Neuro Fuzzy Modeling With Applications In Finance
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Explainable Artificial Intelligence Based on Neuro-Fuzzy Modeling with Applications in Finance
The book proposes techniques, with an emphasis on the financial sector, which will make recommendation systems both accurate and explainable. The vast majority of AI models work like black box models. However, in many applications, e.g., medical diagnosis or venture capital investment recommendations, it is essential to explain the rationale behind AI systems decisions or recommendations. Therefore, the development of artificial intelligence cannot ignore the need for interpretable, transparent, and explainable models. First, the main idea of the explainable recommenders is outlined within the background of neuro-fuzzy systems. In turn, various novel recommenders are proposed, each characterized by achieving high accuracy with a reasonable number of interpretable fuzzy rules. The main part of the book is devoted to a very challenging problem of stock market recommendations. An original concept of the explainable recommender, based on patterns from previous transactions, is developed; it recommends stocks that fit the strategy of investors, and its recommendations are explainable for investment advisers.
Modeling Complex Processes Through Nature-Analogous Methods
This book is an introduction to nature-analogous techniques and related formal methods. For each technique, application examples are provided. It covers cellular automata and Boolean networks, evolutionary algorithms, as well as simulated annealing, fuzzy methods, neural networks, and finally hybrid systems, i.e., combinations of various techniques. Based on the theory of complex dynamic systems, theoretical foundations are also presented, and the similarities of these seemingly very heterogeneous techniques are pointed out. The edition has been revised and expanded with current trends such as ChatGPT.
Explainable Artificial Intelligence in the Digital Sustainability Administration
This book explores current research trends in the context of the explainable artificial intelligence’s impact on the digital sustainability trend while delving into case studies on education, tourism, marketing, and finance. These trends are examined through various case studies utilizing distinct analytical methods. The chapters are expected to support scholars and postgraduate students in furthering their research in this field and in recognizing prospective advancements in the applications of artificial intelligence.