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Siddhartha Bhattacharyya <[log in to unmask]>
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Classification, clustering, and phylogeny estimation
Mon, 8 Sep 2014 10:45:49 -0400
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Call for Chapters: Advanced Research on Hybrid Intelligent Techniques and Applications
Please visit for more details regarding this publication and to submit your chapter proposal.

Dr. Siddhartha Bhattacharyya (RCC Institute of Information Technology, India)
Mr. Pinaki Banerjee (Goldstone Infratech Ltd., India)
Dr. Dipankar Majumdar (RCC Institute of Information Technology, India)
Prof. (Dr.) Paramartha Dutta (Visva-Bharati University, India)

Call for Chapters
Proposals Submission Deadline: September 30, 2014
Full Chapters Due: December 30, 2014


For release in the Advances in Computational Intelligence and Robotics (ACIR) Book Series.

ISSN: 2327-0411

The Advances in Computational Intelligence and Robotics (ACIR) Book Series encourages scholarly discourse on all topics pertaining to evolutionary computing, artificial life, computational intelligence, machine learning, and robotics. ACIR presents the latest research being conducted on diverse topics in intelligence technologies with the goal of advancing knowledge and applications in this rapidly evolving field.

Many real life problems suffer from uncertainty, imprecision, vagueness to name a few. Conventional computing paradigms often fall short of offering solutions to them. Even latest soft computing paradigms are not too robust to handle the situations. Hybrid computing is a paradigm which addresses these issues to a considerable extent. This book is intended to encompass such hybrid computing techniques reported in the literature.

Soft Computing, as the name suggests, deals with the soft meaning of concepts. This is a relatively new computing paradigm which entails a synergistic integration of essentially four other computing paradigms, viz., neural networks, fuzzy logic, rough sets and evolutionary computation, incorporating probabilistic reasoning (belief networks, genetic algorithms and chaotic systems). These computing paradigms are conjoined to provide a framework for flexible information processing applications designed to operate in the real-world. Bezdek referred to this synergism as computational intelligence. According to Prof. Zadeh, soft computing is “an emerging approach to computing, which parallels the remarkable ability of the human mind to reason and learn in an environment of uncertainty and imprecision.” Soft computing technologies are robust by design, and operate by trading off precision for tractability. Since they can handle uncertainty with ease, they conform better to real-world situations and provide lower cost solutions. The four components of soft computing differ from one another in more than one way. They operate either independently or jointly depending on the domain of applications. Hybrid Computing stems from the synergistic integration of the different soft computing tools and techniques. The fusion of these techniques towards achieving enhanced performance and more robust solutions can be achieved through proper hybridization.

An intelligent machine inherits the boon of intelligence by virtue of the various methodologies offered by Soft Computing paradigm encompassing fuzzy and rough set theory, artificial neurocomputing, evolutionary computing, as well as approximate reasoning. At times situation demands in reality where any of the techniques listed above does not provide any comprehensible solution but an effective symbiosis of more than one of the above techniques offers a formidable solution. This gives rise to the advent to several hybrid methodologies. Of late, there is enormous growth of research exploration of injecting elements of intelligence using efficient hybrid techniques. All these initiatives indicate that the individual soft computing techniques do not behave in conflicting manner rather behaves complimentary to one another. In fact, recent reports reveal the inherent strength of such hybridization of computation methods.


To bring a broad spectrum of application domains under the purview of hybrid intelligence so that it is able to trigger further inspiration among various research communities to contribute in their respective fields of applications thereby orienting these application fields towards intelligence.

Once the purpose, as stated above, is achieved a larger number of research communities may be brought under one umbrella to ventilate their ideas in a more structured manner. In that case, the present endeavor may be seen as the beginning of such an effort in bringing various research applications close to one another.

Target Audience

The target audience of the intended book is the relevant research community. To be precise, the book is aimed to establish the missing link between the research standing in the relevant field and that is upcoming. Hybridization would surely and certainly help the readers grasp the essence and utility of the different soft computing techniques in vogue.

The proposed book would come to the benefits of several categories of students and researchers. At the students level, this book can serve as a treatise/reference book for the special papers at the masters level aimed at inspiring possibly future researchers. Newly inducted PhD aspirants would also find the contents of this book useful as far as their compulsory coursework is concerned.

At the researchers' level, those interested in interdisciplinary research would also benefit from the book. After all, the enriched interdisciplinary contents of the book would always be a subject of interest to the faculties, existing research communities and new research aspirants from diverse disciplines of the concerned departments of premier institutes across the globe. This is expected to bring different research backgrounds (due to its cross platform characteristics) close to one another to form effective research groups all over the world. Above all, availability of the book should be ensured to as much universities and research institutes as possible through whatever graceful means it may be.

Recommended Topics

    Computational Intelligence: foundations and principles; neural networks; fuzzy systems; near set; soft set; evolutionary computation; rough sets; swarm intelligence
    Hybridization of intelligent techniques
    Algorithmic, experimental, prototyping and implementation
    Neuro-Fuzzy, Neuro-genetic, Fuzz-genetic, Neuro-fuzz-genetic architectures etc.
    Rough-fuzzy, Rough-neuro, Rough-neuro-fuzz architectures and the like
    Quantum inspired hybrid soft computing architectures
    Mechanical Engineering - Production planning; scheduling and coordination; expert system design; cooperative control; dynamic system analysis; renewable energy systems; robotics and robotic vision engineering problems; process automation
    Power Control and Optimization - Power control; future energy planning and environment; industrial Informatics and planning; scheduling and assignment problems; optimization
    Total Quality Management - TQM intelligent methods; business excellence models; intelligent and virtual CMM
    Machine Intelligence - Data processing, analysis and applications; intelligent systems; emerging computing paradigms
    Nanoscience and Nanoengineering - Artificial intelligence and soft computing techniques; parallel and distributed computing; grid computing and pervasive computing; adaptive reconfigurable architectures
    Mining Engineering - Mine planning and modeling; mine safety methods using intelligent VR and HCI techniques
    Modeling and Simulation - Modeling paradigms; simulation techniques; high performance computing
    Signal Processing – Algorithms, architectures and applications; multidimensional signal processing; radar signal and data processing; adaptive QoS provisioning; VLSI for network processing; embedded reconfigurable architectures; evolvable systems; spread spectrum and CDMA systems; antennas and propagation; mobile ad hoc networking; sensor networks
    Civil Engineering - Modeling and optimization of manufacturing systems and processes; computational fluid dynamics; flood forecasting; analysis of processing of GIS, GPS, remote sensing data; automated inspection
    Computer, Communication, Networking and Information Engineering - Intelligent network management; antenna design, information security; cross-layer optimized wireless networks; pervasive/ ubiquitous computing MEMS systems characterization; Intelligent compiler and interpreter design; expert systems; pattern recognition; image processing
    Optical Engineering - Optical computing; optical image processing; optical testing; optical communication systems and networks; intelligent photonics
    Bioinformatics and Biomedical Engineering - Bio-molecular and phylogenetic databases; Biomedical engineering; biomedical robotics and mechanics; bio-signal processing and analysis; biometrics and bio-measurements
    Ecology and Environmental Engineering - Green energy engineering; environmental pollution and remediation; environmental sustainability and restoration; hazardous substances and detection techniques; air pollution and control; solid waste management
    Engineering Management and Service Sciences - Engineering management; portfolio management; emergency management system; supply chain management; service sciences; converged network and services; e-commerce and e-governance
    Systems Engineering - Industrial automation and robotics; intelligent photonics and lighting systems; computer assisted medical diagnostic systems; unmanned aerospace systems; intelligent control systems; intelligent approaches in system identification/modeling
    Innovative Computing Systems - Intelligent manufacturing systems; quantum inspired soft computing methodologies for signal, image and information processing; medical innovative technologies
    Adaptive Technologies for Sustainable Growth - Soft computing based power systems; bio-medical engineering systems; trends and development in nano technology; wireless sensors and networks
    Theoretical and Applied Sciences - Optimization and analysis of mathematical functions; statistical time series analysis; characterization of chaos theory; theory of fractals and applications to uncertainty management; applications of computational intelligence to atmospheric sciences

Submission Procedure

Researchers and practitioners are invited to submit on or before September 30, 2014, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by October 5, 2014 about the status of their proposals and sent chapter guidelines. Full chapters are expected to be submitted by December 30, 2014. All submitted chapters will be reviewed on a double-blind review basis. Contributors may also be requested to serve as reviewers for this project.

All proposals should be submitted through the "Propose a Chapter" link.

This book is scheduled to be published by IGI Global (formerly Idea Group Inc.), an international academic publisher of the “Information Science Reference” (formerly Idea Group Reference), “Medical Information Science Reference,” “Business Science Reference,” and “Engineering Science Reference” imprints. IGI Global specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, education, social science, medicine and healthcare, business and management, information science and technology, engineering, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit This publication is anticipated to be released in 2015.

Important Dates
September 30, 2014: Proposal Submission Deadline
October 5, 2014: Notification of Acceptance
December 30, 2014: Full Chapter Submission
February 28, 2015: Review Results Returned
April 15, 2015: Final Acceptance Notification
April 30, 2015: Final Chapter Submission

Dr. Siddhartha Bhattacharyya
Department of Information Technology
M: +919830354195
E-mail: [log in to unmask]

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