Iba hitoshi (69 Ergebnisse)

Hardcover/Pappeinband. Zustand: Sehr gut. 330 p. Very good. Shrink wrapped. / Sehr guter Zustand. In Folie verschweißt. Sprache: Englisch Gewicht in Gramm: 798.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New.

Zustand: New. pages cm.

Zustand: New. pp. 317.

Zustand: New. pp. 349.

Zustand: New. In English.

Tankobon Softcover. Zustand: Brand New. Japanese language. 8.27x5.83x0.55 inches. In Stock.

Zustand: New. In English.

Hardcover. Zustand: Brand New. 1st edition. 316 pages. 9.25x6.25x1.00 inches. In Stock.

hardcover. Zustand: Sehr gut. 260 Seiten; 9783642276477.2 Gewicht in Gramm: 1.

Paperback. Zustand: Brand New. 262 pages. 9.25x6.14x0.59 inches. In Stock.

Paperback. Zustand: Brand New. 288 pages. 9.19x6.13x9.21 inches. In Stock.

Kartoniert / Broschiert. Zustand: New. Hitoshi Iba is a Professor at the Graduate School of Information Science and Technology at the University of Tokyo. From 1990 to 1998, he was a senior researcher at the Electro Technical Laboratory (ETL) in Ibaraki, Japan. He is an Assoc.

Tankobon Hardcover. Zustand: Brand New. Japanese language. 8.27x5.91x0.79 inches. In Stock.

Zustand: New. Hitoshi Iba received a PhD from the University of Tokyo, Japan, in 1990. From 1990 to 1998, he was with the Electro Technical Laboratory (ETL) in Ibaraki, Japan. He is currently a Professor at the Department of Information and Communicat.

Taschenbuch. Zustand: Neu. Neuware.

Zustand: New. In English.

Zustand: New. In English.

Zustand: New. Iba, Hitoshi Hasegawa, Yoshihiko Paul, Topon KumarWhat do financial data prediction, day-trading rule development, and bio-marker selection have in common? They are just a few of the tasks that could potentially be resolved with genetic program.

Zustand: New. In English.

Zustand: New. Hitoshi IbaSwarm-based multi-agent simulation leads to better modeling of tasks in biology, engineering, economics, art, and many other areas. It also facilitates an understanding of complicated phenomena that cannot be solved analytically. A.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Taschenbuch. Zustand: Neu. Neuware - This book provides theoretical and practical knowledge about swarm and evolutionary approach of generative AI and Large Language Models (LLMs). The development of such tools contributes to better optimizing methodologies with the integration of several machinelearning and deep learning techniques. In particular, it discusses how the 'emergence' concept can contribute to the improvement of AI.The book aims to model human cognitive f unction in terms of 'emergence' and to explain the feasibility of AI. To this end, it focuses on human perceptions of 'utility.' It describes the emergence of various cognitive errors, and irrational behaviours in the multiobjective situations. It also reviews the cognitive differences and similarities between humans and LLMs. Such studies are important when applying LLMs to real-world tasks that involve human cognition, e.g., financial engineering and market issues.The book describes the intelligent behaviour of living organisms. This is to clarify how to achieve AI in the direction of artificial life. It describes sexual selection, which is a well-known natural phenomenon that troubled Darwin, i.e., why evolutionarily useless items evolved such as peacock feathers and moose antlers etc. The book shows how sexual selection is extended as 'novelty search' for the application of generative AI, i.e., the image generation with diffusion model. Real-world applications are emphasised. Empirical examples from real-world data show how the concept of deep swarm and evolution is successfully applied when addressing tasks from such recent fields as robotics, e-commerce Web Shop and image generation etc.…

Paperback. Zustand: Brand New. 349 pages. 9.21x6.14x0.79 inches. In Stock.

Taschenbuch. Zustand: Neu. Neuware.

Zustand: New.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 'Practical Applications of Evolutionary Computation to Financial Engineering' presents the state of the art techniques in Financial Engineering using recent results in Machine Learning and Evolutionary Computation. This book bridges the gap between academics in computer science and traders and explains the basic ideas of the proposed systems and the financial problems in ways that can be understood by readers without previous knowledge on either of the fields. To cement the ideas discussed in the book, software packages are offered that implement the systems described within. The book is structured so that each chapter can be read independently from the others. Chapters 1 and 2 describe evolutionary computation. The third chapter is an introduction to financial engineering problems for readers who are unfamiliar with this area. The following chapters each deal, in turn, with a different problem in the financial engineering field describing each problem in detail and focusing on solutions based on evolutionary computation. Finally, the two appendixes describe software packages that implement the solutions discussed in this book, including installation manuals and parameter explanations.…

Zustand: Gut. Zustand: Gut | Seiten: 318 | Sprache: Englisch | Produktart: Bücher | This book delivers theoretical and practical knowledge of Genetic Algorithms (GA) for the purpose of practical applications. It provides a methodology for a GA-based search strategy with the integration of several Alife and AI techniques, such as memetic concepts, swarm intelligence and foraging strategies. The development of such tools contributes to better optimizing methodologies when addressing tasks from areas such as robotics, financial forecasting and data mining in bioinformatics. The emphasis of this book is applicability to real-world tasks. Tasks from application areas optimization of the trading rule in foreign exchange (FX) and stock prices, economic load dispatch in power system, exit/door placement for evacuation planning, and gene regulatory network inference in bioinformatics are studied, and the resultant empirical investigations demonstrate how successful the proposed approaches are when solving real-world tasks of great importance.…