Guest Editors
Dr. Nguyen Van Thanh, Van Lang University, Vietnam.
Dr. Phan Nguyen Ky Phuc, International University, Vietnam.
Dr. Nguyen Huu Tho, Nguyen Tat Thanh University.
Summary
The
Earth’s climate and environment have been experiencing drastic changes in the
past few decades. As our fossil fuels resources continue to deplete and our way
of life being increasingly threatened, researchers and policy makers are
urgently searching for new ways to preserve our limited resources as well as to
improve the current environmental conditions. The answer to these problems can
be found through soft computing, which has been constantly evolving as a faster
pace than ever before with new techniques and applications.
Soft
computing as opposed to hard computing, work with approximate models and gives
solutions to complex real-life problems. Unlike hard computing, soft computing
is tolerant of imprecision, uncertainty, partial truth, and approximations.
This allows soft computing to be successfully applied many sectors and
industries. Soft computing offers new approaches, which are characterized by
hybrid solutions and intelligent methods, to existing problems. These
approaches construct effective solutions to many problems based on axiomatic
mathematical theories and systems.
In
the renewable energy field, soft-computing approaches can be applied
independently or in conjunction with other approaches to solve managerial and
technical problems such as decision support, risk management, energy efficiency
evaluation, group decision making, public policies development, project
development process, process design, etc.
This
Special Issue on Axioms in Soft computing for Renewable Energy development aims
to collect high-quality research studies addressing renewable energy related
problems, focusing on the application of soft computing techniques in the
Renewable Energy field. The special issue focuses on the application
soft-computing classical approaches such as fuzzy logic, support vector
machines, genetic algorithms, artificial neural networks, machine learning, and
rough sets in the framework of optimization, multicriteria decision-making,
game theory, outranking, and others.
Keywords
Multi-Criteria Decision Making (MCDM)
Renewable Systems Design
Fuzzy Sets
Genetic Algorithms
Neural Network
Fuzzy Neural Network
Expert Systems
Machine Learning
Renewable Energy Project Management
Sustainable Projects
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