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Probabilistic modeling represents a subject arising in many branches of mathematics, economics, and computer science. Such modeling connects pure mathematics with applied sciences. Similarly, data analyzing and statistics are situated on the border between pure mathematics and applied sciences. Therefore, when probabilistic modeling meets statistics, it is a very interesting occasion that has gained much research recently. With the increase of these technologies in life and work, it has become somewhat essential in the workplace to have planning, timetabling, scheduling, decision making, optimization, simulation, data analysis, and risk analysis and process modeling. However, there are still...
Shape representation and reconstruction is a vital aspect of modern computer science applications. New modeling methods and techniques can significantly optimize these processes. Probabilistic Nodes Combination (PNC) for Object Modeling and Contour Reconstruction is an innovative reference source that examines the latest trends in 2D curve interpolation and modeling methodologies. Focusing on a range of pertinent topics such as 3D surface modeling, high-dimensional data, and numerical methods, this is an ideal publication for programmers, researchers, students, and practitioners interested in emerging methods in object modeling and contour reconstruction.
The two-volume set LNAI 8467 and LNAI 8468 constitutes the refereed proceedings of the 13th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2014, held in Zakopane, Poland in June 2014. The 139 revised full papers presented in the volumes, were carefully reviewed and selected from 331 submissions. The 69 papers included in the first volume are focused on the following topical sections: Neural Networks and Their Applications, Fuzzy Systems and Their Applications, Evolutionary Algorithms and Their Applications, Classification and Estimation, Computer Vision, Image and Speech Analysis and Special Session 3: Intelligent Methods in Databases. The 71 papers in the second volume are organized in the following subjects: Data Mining, Bioinformatics, Biometrics and Medical Applications, Agent Systems, Robotics and Control, Artificial Intelligence in Modeling and Simulation, Various Problems of Artificial Intelligence, Special Session 2: Machine Learning for Visual Information Analysis and Security, Special Session 1: Applications and Properties of Fuzzy Reasoning and Calculus and Clustering.
Probabilistic modeling represents a subject spanning many branches of mathematics, economics, and computer science to connect pure mathematics with applied sciences. Operational research also relies on this connection to enable the improvement of business functions and decision making. Analyzing Risk through Probabilistic Modeling in Operations Research is an authoritative reference publication discussing the various challenges in management and decision science. Featuring exhaustive coverage on a range of topics within operational research including, but not limited to, decision analysis, data mining, process modeling, probabilistic interpolation and extrapolation, and optimization methods, this book is an essential reference source for decision makers, academicians, researchers, advanced-level students, technology developers, and government officials interested in the implementation of probabilistic modeling in various business applications.
As technology continues to become more sophisticated, a computer’s ability to understand, interpret, and manipulate natural language is also accelerating. Persistent research in the field of natural language processing enables an understanding of the world around us, in addition to opportunities for manmade computing to mirror natural language processes that have existed for centuries. Natural Language Processing: Concepts, Methodologies, Tools, and Applications is a vital reference source on the latest concepts, processes, and techniques for communication between computers and humans. Highlighting a range of topics such as machine learning, computational linguistics, and semantic analysis, this multi-volume book is ideally designed for computer engineers, computer and software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the latest trends in the field of natural language processing.
The fields of computer vision and image processing are constantly evolving as new research and applications in these areas emerge. Staying abreast of the most up-to-date developments in this field is necessary in order to promote further research and apply these developments in real-world settings. Computer Vision: Concepts, Methodologies, Tools, and Applications is an innovative reference source for the latest academic material on development of computers for gaining understanding about videos and digital images. Highlighting a range of topics, such as computational models, machine learning, and image processing, this multi-volume book is ideally designed for academicians, technology professionals, students, and researchers interested in uncovering the latest innovations in the field.
This volume constitutes selected papers presented at the 28th International Conference on Systems, Signals and Image Processing, IWSSIP 2021, held in Bratislava, Slovakia, in June 2021. Due to the COVID-19 pandemic the conference was held online. The presented 14 full and 5 short papers were thorougly reviewed and selected from the 76 submissions. The papers focus on various aspects of advanced signal processing in different scientific areas, including filter design, Fourier and other transforms, feature extraction, machine learning and system adaptation to user-oriented products like 5G networks, IoT, virtual teleport or tele-surgery operations.
Although computational intelligence and soft computing are both well-known fields, using computational intelligence and soft computing in conjunction is an emerging concept. This combination can effectively be used in practical areas of various fields of research. Applied Computational Intelligence and Soft Computing in Engineering is an essential reference work featuring the latest scholarly research on the concepts, paradigms, and algorithms of computational intelligence and its constituent methodologies such as evolutionary computation, neural networks, and fuzzy logic. Including coverage on a broad range of topics and perspectives such as cloud computing, sampling in optimization, and swarm intelligence, this publication is ideally designed for engineers, academicians, technology developers, researchers, and students seeking current research on the benefits of applying computation intelligence techniques to engineering and technology.
This book is a collection of selected research papers presented at the 2023 4th International Conference on Artificial Intelligence in Education Technology (AIET 2023), held in Berlin, Germany, on June 30 - July 2, 2023. AIET establishes a platform for AI in education researchers to present research, exchange innovative ideas, propose new models, as well as demonstrate advanced methodologies and novel systems. It is a timely and up-to-date publication responsive to the rapid development of AI technologies, practices and their increasingly complex interplay with the education domain. It promotes the cross-fertilisation of knowledge and ideas from researchers in various fields to construct the...