Complimentary Address

2017 ◽  
Vol 21 (1) ◽  
pp. 6-6
Author(s):  
Imre Rudas ◽  
Keyword(s):  
Soft Computing ◽  
Computational Intelligence ◽  
Fuzzy Inference ◽  
Leading Edge ◽  
Research Field ◽  
Green Energy ◽  
Power Grids ◽  
Biologically Inspired ◽  
Inference Systems ◽  
Self Driving Cars

  First of all it is my great pleasure to congratulate to the 20th anniversary of the Journal of Advanced Computational Intelligence and Intelligent Informatics (JACIII). The first volume of the journal was published in 1997 – and now twenty years later we reached the Vol. 21. Over these years JACIII was one of the forefront and determining journals of soft computing and intelligent informatics and focused to the most up-to-date topic despite the fast vary and evolvement of this research field through its regular and special sessions. One of the greatest merit of the journal is that it is able be serve as a common platform for the most relevant researchers and societies in order to expand the boundaries of many related fields including Fuzzy Logic, Neural Networks, Genetic and Evolutionary Computation, Biologically-Inspired Computation Systems and so on.   In these days the most up-coming challenges are connected to the topics of JACIII including the current special issue as well. Self-driving cars, Wearables, Internet-of-Things and many other phenomena are imaginable with the advanced <em>Computational Intelligence</em> behind the rooftop. Expert- and decision-making systems and effective usage of big data request the highly developed <em>Fuzzy Inference Systems</em>. Monitoring of social media in order to get useful information regarding the habits of human users and artificial robots cannot be realized without <em>Web and Artificial Intelligence</em>. Soft-computing based methods and many other intelligent and automated solutions are needed for eligible <em>Data mining</em> – and for the further preparation of the gathered data. Moreover, the demands of future smart city concepts, developed green energy producing solutions and connected power grids present the scientists with specific challenges whereon <em>Smart Grid</em> concept can be the only answer.   I would like to invite the Reader to an interesting reading which deals with the aforementioned challenges and scenarios.   Furthermore, I hope that JACIII can continue its contribution to the leading-edge research and we can celebrate the 30th anniversary together as well.

CREATION OF A SOFTWARE INTERFACE TO SUPPORT THE SOLUTION OF RESEARCH PROBLEMS IN THE FIELD OF SOFT COMPUTING USING THE PHYTON SCIKIT-FUZZY LIBRARY

2021 ◽  
Vol 1 (6) ◽  
pp. 61-80
Author(s):  
Nikolay A. Toichkin ◽  
◽  
Valery N. Bogatikov ◽  
Keyword(s):  
Soft Computing ◽  
Computational Experiment ◽  
Fuzzy Inference ◽  
Fuzzy Inference Systems ◽  
Technological Parameters ◽  
Software Module ◽  
Software Interface ◽  
Research Problems ◽  
Inference Systems

The article discusses the issue of creating a software interface for developing fuzzy inference systems using the ScikitFuzzy library. With the help of the developed software module, a computational experiment was carried out to calculate the fuzzy output of the values of technological parameters for a fourcase evaporator unit, which is part of the evaporation shop of chlorine production.

E-Banking Operational Risk Management using Soft Computing Tools

2012 ◽  
pp. 176-202 ◽  
Author(s):  
Rita E Ochuko ◽  
Andrea Cullen ◽  
Daniel Neagu
Keyword(s):  
Risk Management ◽  
Soft Computing ◽  
Fuzzy Inference ◽  
Operational Risk ◽  
Management Tools ◽  
Modeling Tools ◽  
Market Opportunities ◽  
Inference Systems ◽  
Tools And Techniques ◽  
Improved Technology

Electronic banking (E-banking) systems provide a promising solution for breaking geographical, industrial, and regulatory barriers. Improved technology could help with creating anytime, anywhere services and new market opportunities, but does not necessarily ensure a risk-free transaction environment. A main aim for E-banking adopters is to include E-banking risk management to their overall risk management strategy. They must identify the tools and techniques available for managing such risk. In this chapter we provide an overview of E-banking and identify the various risks which exist within the system. The chapter focuses on analyzing state-of-the-art risk management tools and techniques, paying attention to models for internally managing E-banking operational risk. It discusses several soft computing techniques applied to E-banking operational risk as causal modeling tools. The tools include: Decision Trees, Artificial Neural Networks (ANN), Fuzzy Inference Systems, and Bayesian Networks. Some examples are presented to describe the models developed.

scholarly journals Beyond analogy: A model of bioinspiration for creative design

2016 ◽  
Vol 30 (2) ◽  
pp. 159-170 ◽  
Author(s):  
Camila Freitas Salgueiredo ◽  
Armand Hatchuel
Keyword(s):  
Design Process ◽  
Design Theory ◽  
Leading Edge ◽  
Knowledge Bases ◽  
Biologically Inspired ◽  
Concept Knowledge ◽  
Bioinspired Design ◽  
Aerodynamic Properties ◽  
Biologically Inspired Design ◽  
The Impact

AbstractIs biologically inspired design only an analogical transfer from biology to engineering? Actually, nature does not always bring “hands-on” solutions that can be analogically applied in classic engineering. Then, what are the different operations that are involved in the bioinspiration process and what are the conditions allowing this process to produce a bioinspired design? In this paper, we model the whole design process in which bioinspiration is only one element. To build this model, we use a general design theory, concept–knowledge theory, because it allows one to capture analogy as well as all other knowledge changes that lead to the design of a bioinspired solution. We ground this model on well-described examples of biologically inspired designs available in the scientific literature. These examples include Flectofin®, a hingeless flapping mechanism conceived for façade shading, and WhalePower technology, the introduction of bumps on the leading edge of airfoils to improve aerodynamic properties. Our modeling disentangles the analogical aspects of the biologically inspired design process, and highlights the expansions occurring in both knowledge bases, scientific (nonbiological) and biological, as well as the impact of these expansions in the generation of new concepts (concept partitioning). This model also shows that bioinspired design requires a special form of collaboration between engineers and biologists. Contrasting with the classic one-way transfer between biology and engineering that is assumed in the literature, the concept–knowledge framework shows that these collaborations must be “mutually inspirational” because both biological and engineering knowledge expansions are needed to reach a novel solution.

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