Machine Learning Emulation in Nature-inspired Computation Systems
نویسندگان
چکیده
The whole frame of nature_inspired computation systems is inquired into, the characteristics of machine learning in nature_inspired computation systems are researched, and a particular scheme on machine learning in nature_inspired computation systems is designed with environment being gathered present data; study unit adopting fuzzy optimizatio algorithm based on genetic algorithm; knowledge base adopting fuzzy optimization BP neural networks; executive unit being complicated industry process. The fuzzy optimizatio learning algorithm of fuzzy optimization BP neural networks is built, the flow chart of the algorithm is constructed, and the emulation test is made. At last, the design criteria of flash metal comsuption are obtained, and the stability of the algorithm is verified through this example. The result shows that machine learning makes nature_inspired computation systems be able to gain know; edge automatically, their quality improved, their intelligent level advanced, and machine learning will greatly influence the memory mode, information input mode and system structures of nature_inspired computation systems.
منابع مشابه
Emulation of an unconventional model of computation in Java
This paper describes the emulation of an unconventional model of computation inspired by the field of optical computing. The model could be described as a random access machine with registers that hold continuous twodimensional images. Our development employed a combination of eXtreme Programming, unit and integration testing with junit, and design patterns. In the final product we implemented ...
متن کاملSemantic Preserving Data Reduction using Artificial Immune Systems
Artificial Immune Systems (AIS) can be defined as soft computing systems inspired by immune system of vertebrates. Immune system is an adaptive pattern recognition system. AIS have been used in pattern recognition, machine learning, optimization and clustering. Feature reduction refers to the problem of selecting those input features that are most predictive of a given outcome; a problem encoun...
متن کاملSpecial Issue on Hybrid Learning Machines
The concept of Machine Intelligence (MI) is complex, and thus many theories and definitions have emerged recently. Last few decades have seen a new era of machine intelligence focusing on the principles, theoretical aspects, and design methodology of algorithms gleaned from nature and biology. Examples are artificial neural networks inspired by mammalian neural systems, evolutionary computation...
متن کاملImproved teaching–learning-based and JAYA optimization algorithms for solving flexible flow shop scheduling problems
Flexible flow shop (or a hybrid flow shop) scheduling problem is an extension of classical flow shop scheduling problem. In a simple flow shop configuration, a job having ‘g’ operations is performed on ‘g’ operation centres (stages) with each stage having only one machine. If any stage contains more than one machine for providing alternate processing facility, then the problem...
متن کاملGenerative NeuroEvolution for Deep Learning
An important goal for the machine learning (ML) community is to create approaches that can learn solutions with human-level capability. One domain where humans have held a significant advantage is visual processing. A significant approach to addressing this gap has been machine learning approaches that are inspired from the natural systems, such as artificial neural networks (ANNs), evolutionar...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Computer and Information Science
دوره 2 شماره
صفحات -
تاریخ انتشار 2009