Soft computing (SC) is a collection of methodologies that are trying to cope with the main disadvantage of the conventional (hard) computing: the poor performances when working in uncertain conditions. The fundamental idea of soft computing is to emulate the human like reasoning. The classic constituents of SC are fuzzy logic, neural network theory and probabilistic reasoning, but new methods are continuously emerging: belief networks, genetic algorithms, anytime algorithms, chaos theory, some parts of learning theory, etc.

Novel soft computing methods:

Fuzzy Logic, Neural Networks, Belief Functions,  Evidence Theory, Evolutionary Computation, Anytime Algorithms, Hybrid Systems, Probabilistic Reasoning, Possibilistic Reasoning, Clustering Techniques, Feature Selection Methods, Adaptive Modelling, Knowledge Discovery Methods, Novel Learning Algorithms.

Intelligent control systems:

Model-Predictive Control, Adaptive and Optimal Control, Intelligent Control Systems, Robotics and Automation, Fault Diagnosis, Intelligent Agents & Multiagent Systems, Industrial Automation, Hybrid Control Systems.

Computational Intelligence for Bioinformatics and Biomedical applications:

Soft Computing Methods for Biological Data Analysis and Knowledge Discovery, Mining the Human Genome, Brain Data Analysis and Modeling, Gene Expression Data Analysis and Disease Profiling, Protein Function Prediction, Adaptive Integrated Systems for Medical and Health Applications.

Optimization and Prediction:

Multi-criteria Optimization, Signal Processing, Time Series Analysis & Prediction, System Identification, Data Mining & Knowledge Discovery, Intelligent Information Systems, Image Processing, Parallel Computing Applications in Identification & Control, Pattern Recognition, Clustering, Classification, Complex Systems.

Decision Support Systems:

Intelligent Databases & Information Retrieval, Case-Based Reasoning, Decision Analysis, Dynamic Systems Modeling, Decision Support Systems, Qualitative and Approximate-Reasoning Modeling, Multiple Criteria Decision Aid.

Intelligent Systems for Signal Processing:

Signal Processing, Speech Recognition, Image Analysis, Video Data Modeling, Diagnostics, Uncertainty-handling, Anytime Algorithms, Sensors, Distributed Measurement, Tool Integration for Better Performance, Virtual Systems, Intelligent Space, Applications

Smart Vehicular Technology, Transportation, Communication and Applications

Intelligent Transportation Systems and Big Data Applications, Positioning, Navigation, and Satellite Networks, Smart Vehicular Communication Networks, Security, Vehicular Electronics

“Aurel Vlaicu” University of Arad

University of Rwanda

Lovely Professional University

African Center of Excellence in Internet of Things

Institute of Computer Science of the Romanian Academy – Iasi Branch

 (AGIR) – Arad Section

Societatea Română de Automatică și Informatică Tehnică, filiala ARAD

APTIV

IEEE CIS Chapter , Romania

IEEE Romania Section

BTM Resources

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