Fraud remains a pervasive global issue, affecting individuals and organizations alike. In the modern technology-driven landscape, role of machine learning (ML) artificial intelligence (AI) has become paramount in combating fraud across various sectors. This article critically examines traditional prevention methods, highlighting their limitations face ever-evolving fraudulent tactics. It furthe...

Explainable artificial intelligence (XAI) is a crucially important aspect of improving trust and reliability intelligent machine learning (AI/ML) systems. In this special issue, we have included diverse group articles addressing different aspects XAI in variety domains. From real-time systems to human-in-the-loop fault detection, the here looked into AI explanation from varying perspectives for...

Recent years have witnessed the widespread popularity of Internet things (IoT). By providing sufficient data for model training and inference, IoT has promoted development artificial intelligence (AI) to a great extent. Under this background trend, traditional cloud computing may nevertheless encounter many problems in independently tackling massive generated by meeting corresponding practical ...

Humans and other animals are often touted as examples of systems that possess general intelligence. However, rarely if ever do they achieve high levels of intelligence and autonomy on their own: they are raised by parents and caregivers in a society with peers and seniors, who serve as teachers and examples. Current methods for developing artificial learning systems typically do not account for...

Computational Intelligence Machine Learning (CIML) is a mature discipline with a wide range of potential applications. Many state-of-the-art methods developed in CIML, however, remain unused outside the relatively small groups of researchers in which they originate. This can be attributed to lack of communication between disciplines, difficulty of use, availability, and limited understanding of...

Aiming to create a cognitive system with human-level intelligence is as different from normal scientific objectives as reaching artificial immortality is to the goals of modern medicine. Most researchers in artificial intelligence, along with the institutions that support them, advocate that AI research should conform to normal scientific standards and methods. I argue that these are often inci...

In recent years, tendency to renewable energy resources has increased considerably in order obtain cleaner energy. The effect of the decisions taken by artificial intelligence models on efficiency is very important transformation these resources. With eXplainable Artificial Intelligence (XAI), various methods have been developed for trust, transparency and decision making models, but more need ...

1. Review of Subject Articles 1.1.General Principles and Purposes of Computational Intelligence 1.2.Neural Networks 1.3.Simulated Annealing 1.4.Adaptive Systems 1.5.Biological Intelligence and Computational Intelligence 2. Introduction 3. Computability, Decidability, and Complexity 4. Computational Intelligence and Knowledge-based Systems 4.1.Beginning of Artificial Intelligence (AI) 4.2.Knowle...

In the artificial intelligence field, learning often corresponds to changing the param-eters of a parameterized function. A learning rule is an algorithm or mathematicalexpression that specifies precisely how the parameters should be changed. Whencreating an artificial intelligence system, we must make two decisions: what repre-sentation should be used (i.e., what parameterized ...