عنوان

Artificial cognitive architecture with self-learning and self-optimization capabilities :

شابک

3030039498

شابک

3030039501

شابک

9783030039493

شابک

9783030039509

شابک اشتباه

303003948X

شابک اشتباه

9783030039486

عنوان اصلي

Artificial cognitive architecture with self-learning and self-optimization capabilities :

نام عام مواد

[Book]

ساير اطلاعات عنواني

case studies in micromachining processes /

نام نخستين پديدآور

Gerardo Beruvides.

محل نشرو پخش و غیره

Cham, Switzerland :

نام ناشر، پخش کننده و غيره

Springer,

تاریخ نشرو بخش و غیره

[2019]

تاریخ نشرو بخش و غیره

©2019

نام خاص و کميت اثر

1 online resource

عنوان فروست

Springer theses : recognizing outstanding Ph. D. research

متن يادداشت

Includes bibliographical references.

متن يادداشت

Introduction -- Modeling Techniques for Micromachining Processes -- Cross Entropy Multi-Objectve Optimization Algorithm -- Artificial Cognitive Architecture Design and Implementation.

بدون عنوان

0

متن يادداشت

This book introduces three key issues: (i) development of a gradient-free method to enable multi-objective self-optimization; (ii) development of a reinforcement learning strategy to carry out self-learning and finally, (iii) experimental evaluation and validation in two micromachining processes (i.e., micro-milling and micro-drilling). The computational architecture (modular, network and reconfigurable for real-time monitoring and control) takes into account the analysis of different types of sensors, processing strategies and methodologies for extracting behavior patterns from representative process' signals. The reconfiguration capability and portability of this architecture are supported by two major levels: the cognitive level (core) and the executive level (direct data exchange with the process). At the same time, the architecture includes different operating modes that interact with the process to be monitored and/or controlled. The cognitive level includes three fundamental modes such as modeling, optimization and learning, which are necessary for decision-making (in the form of control signals) and for the real-time experimental characterization of complex processes. In the specific case of the micromachining processes, a series of models based on linear regression, nonlinear regression and artificial intelligence techniques were obtained. On the other hand, the executive level has a constant interaction with the process to be monitored and/or controlled. This level receives the configuration and parameterization from the cognitive level to perform the desired monitoring and control tasks.

منبع سفارش / آدرس اشتراک

Springer Nature

شماره انبار

com.springer.onix.9783030039493

عنوان

Artificial cognitive architecture with self-learning and self-optimization capabilities.

شماره استاندارد بين المللي کتاب و موسيقي

9783030039486

موضوع مستند نشده

Artificial intelligence.

موضوع مستند نشده

Cognitive science.

موضوع مستند نشده

Machine learning.

موضوع مستند نشده

Mathematical optimization.

موضوع مستند نشده

Micromachining.

موضوع مستند نشده

Artificial intelligence.

موضوع مستند نشده

Cognitive science.

موضوع مستند نشده

COMPUTERS-- General.

موضوع مستند نشده

Machine learning.

موضوع مستند نشده

Mathematical optimization.

موضوع مستند نشده

Micromachining.

موضوع مستند نشده

COM-- 000000

موضوع مستند نشده

TJFM

موضوع مستند نشده

TJFM

شماره

ويراست

شماره رده

مستند نام اشخاص تاييد نشده

Beruvides, Gerardo

تاريخ عمليات

20200823080001.0

قواعد فهرست نويسي ( بخش توصيفي )

pn

نام الکترونيکي

نوع ماده

[Book]

تكميل شده

Y