Introduction
Soft computing (SC)
consists of several computing paradigms, including Neural Networks (NN), Fuzzy
set theory, Rough sets, Optimization Techniques, Geometric modeling,
Approximate Reasoning (AR), Cognitive models and Evolutionary Algorithms (EA).
The integration of these constituent methodologies forms the core of SC. In
addition to the synergy allows SC to incorporate human knowledge effectively
which deal with imprecision and uncertainty and learn to adapt to
unknown/changing environments for better performance. Together with the recent
technologies, SC and its applications exert unprecedented influence on
intelligent systems that mimic human intelligence in thinking, learning,
reasoning, and many other aspects.
Knowledge engineering (KE) deals with knowledge acquisition, representation, validation, inferencing, explanation, and maintenance, has made significant progress recently, owing to the indefatigable efforts of researchers. The hot topics of data mining, knowledge/data discovery and Big-Data analytics have injected new life into the classical AI world.
It is obvious that soft computing and knowledge engineering are expected to fulfill some common targets in materializing machine intelligence. In recent trends, many researchers of SC have applied their techniques in solving KE problems, and researchers of KE have adopted SC methodologies to enhance KE applications. The cooperation of these two disciplines is not only extending the application of SC, but also introducing new innovation to KE.
KE has been influenced and extended by SC. The participant is expected to have a basic knowledge of fuzzy/rough sets, neural networks, Evolutionary techniques and Big-Data in IT Industry for developing Knowledge based intelligent agents.
The workshop will cover the underlying principles of Soft Computing and its applications in different areas to develop intelligent agents as a process of Knowledge engineering frameworks. The workshop is aimed for the students as well as for the professionals working either in industry or in academics.
The Workshop is organized by Department of Computer Applications, Prasad V. Potluri Siddhartha Institute of Technology (Autonomous) in association with Soft Computing Society- PVPSIT, Sponsored by Siddhartha Academy of General & Technical Education
Knowledge engineering (KE) deals with knowledge acquisition, representation, validation, inferencing, explanation, and maintenance, has made significant progress recently, owing to the indefatigable efforts of researchers. The hot topics of data mining, knowledge/data discovery and Big-Data analytics have injected new life into the classical AI world.
It is obvious that soft computing and knowledge engineering are expected to fulfill some common targets in materializing machine intelligence. In recent trends, many researchers of SC have applied their techniques in solving KE problems, and researchers of KE have adopted SC methodologies to enhance KE applications. The cooperation of these two disciplines is not only extending the application of SC, but also introducing new innovation to KE.
KE has been influenced and extended by SC. The participant is expected to have a basic knowledge of fuzzy/rough sets, neural networks, Evolutionary techniques and Big-Data in IT Industry for developing Knowledge based intelligent agents.
The workshop will cover the underlying principles of Soft Computing and its applications in different areas to develop intelligent agents as a process of Knowledge engineering frameworks. The workshop is aimed for the students as well as for the professionals working either in industry or in academics.
The Workshop is organized by Department of Computer Applications, Prasad V. Potluri Siddhartha Institute of Technology (Autonomous) in association with Soft Computing Society- PVPSIT, Sponsored by Siddhartha Academy of General & Technical Education
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