[AISWorld] Contents of International Journal of Intelligent Information Technologies (IJIIT) - Vol. 12, No. 1

[Vijayan Sugumaran]

The contents of the latest issue of:
International Journal of Intelligent Information Technologies (IJIIT)
Volume 12, Issue 1, January - March 2016
Published: Quarterly in Print and Electronically
ISSN: 1548-3657; EISSN: 1548-3665; 
Published by IGI Global Publishing, Hershey, USA
www.igi-global.com/ijiit
<http://www.igi-global.com/journal/international-journal-intelligent-informa
tion-technologies/1089> 

Editor-in-Chief: Vijayan Sugumaran (Oakland University, USA)

Note: There are no submission or acceptance fees for manuscripts submitted
to the International Journal of Intelligent Information Technologies
(IJIIT). All manuscripts are accepted based on a double-blind peer review
editorial process.

GUEST EDITORIAL PREFACE

The Impact of Fuzzy Set and Intuitionistic Fuzzy Approaches in Relation to
Organizational Decision Making

Arun Kumar Sangaiah (School of Computing Science and Engineering, VIT
University, Vellore, India), Jinhai Li (Faculty of Science, Kunming
University of Science and Technology, Kunming, China), Tsung-Han Chang (Kao
Yuan University, Kaohsiung, Taiwan)

To obtain a copy of the Guest Editorial Preface, click on the link below.
www.igi-global.com/pdf.aspx?tid=145772
<http://www.igi-global.com/pdf.aspx?tid=145772&ptid=131650&ctid=15&t=The%20I
mpact%20of%20Fuzzy%20Set%20and%20Intuitionistic%20Fuzzy%20Approaches%20in%20
Relation%20to%20Organizational%20Decision%20Making>
&ptid=131650&ctid=15&t=The Impact of Fuzzy Set and Intuitionistic Fuzzy
Approaches in Relation to Organizational Decision Making

ARTICLE 1

A Fuzzy-Based Approach to Support Decision Making in Complex Military
Environments

Timothy P. Hanratty (US Army Research Laboratory, Aberdeen Proving Ground,
MD, USA), E. Allison Newcomb (Towson University, Towson, MD, USA), Robert J.
Hammell II (Towson University, Towson, MD, USA), John T. Richardson (US Army
Research Laboratory, Aberdeen Proving Ground, MD, USA), Mark R. Mittrick (US
Army Research Laboratory, Aberdeen Proving Ground, MD, USA)

Data for military intelligence operations are increasing at astronomical
rates. As a result, significant cognitive and temporal resources are
required to determine which information is relevant to a particular
situation. Soft computing techniques, such as fuzzy logic, have recently
been applied toward decision support systems to support military
intelligence analysts in selecting relevant and reliable data within the
military decision making process. This article examines the development of
one such system and its evaluation using a constructive simulation and human
performance model to provided critical understanding of how this conceptual
information system might interact with personnel, organizational, and system
architectures. In addition, similarities between military intelligence
analysts and cyber intelligence analysts are detailed along with a plan for
transitioning the current fuzzy-based system to the cyber security domain.

To obtain a copy of the entire article, click on the link below.
www.igi-global.com/article/a-fuzzy-based-approach-to-support-decision-making
-in-complex-military-environments/145775
<http://www.igi-global.com/article/a-fuzzy-based-approach-to-support-decisio
n-making-in-complex-military-environments/145775> 

To read a PDF sample of this article, click on the link below.
www.igi-global.com/viewtitlesample.aspx?id=145775
<http://www.igi-global.com/viewtitlesample.aspx?id=145775> 

ARTICLE 2

Fuzzy based Quantum Genetic Algorithm for Project Team Formation

Arish Pitchai (National Institute of Technology Tiruchirappalli,
Tiruchirappalli, India), Reddy A. V. (National Institute of Technology
Tiruchirappalli, Tiruchirappalli, India), Nickolas Savarimuthu (National
Institute of Technology Tiruchirappalli, Tiruchirappalli, India)

Formation of an effective project team plays an important role in successful
completion of the projects in organizations. As the computation involved in
this task grows exponentially with the growth in the size of personnel,
manual implementation is of no use. Decision support systems (DSS) developed
by specialized consultants help large organizations in personnel selection
process. Since, the given problem can be modelled as a combinatorial
optimization problem, Genetic Algorithmic approach is preferred in building
the decision making software. Fuzzy descriptors are being used to facilitate
the flexible requirement specifications that indicates required team member
skills. The Quantum Walk based Genetic Algorithm (QWGA) is proposed in this
paper to identify near optimal teams that optimizes the fuzzy criteria
obtained from the initial team requirements. Efficiency of the proposed
design is tested on a variety of artificially constructed instances. The
results prove that the proposed optimization algorithm is practical and
effective.

To obtain a copy of the entire article, click on the link below.
www.igi-global.com/article/fuzzy-based-quantum-genetic-algorithm-for-project
-team-formation/145776
<http://www.igi-global.com/article/fuzzy-based-quantum-genetic-algorithm-for
-project-team-formation/145776> 

To read a PDF sample of this article, click on the link below.
www.igi-global.com/viewtitlesample.aspx?id=145776
<http://www.igi-global.com/viewtitlesample.aspx?id=145776> 

ARTICLE 3

Comparative Analysis of Neural Network and Fuzzy Logic Techniques in Credit
Risk Evaluation

Asogbon Mojisola Grace (Department of Computer Science, Federal University
of Technology Akure, Akure, Nigeria), Samuel Oluwarotimi Williams (Institute
of Biomedical and Health Engineering, Shenzhen Institutes of Advanced
Technology, Chinese Academy of Sciences, China)

Credit risk evaluation techniques that aid effective decisions in credit
lending are of great importance to the financial and banking industries.
Such techniques assist credit managers to minimize the risks often
associated with wrong decision making. Several techniques have been
developed in the time past for credit risk evaluation and these techniques
suffer from one form of limitation or the other. Recently, powerful soft
computing tools have been proposed for problem solving among which are the
neural networks and fuzzy logic. In this study, a neural network based on
backpropagation learning algorithm and a fuzzy inference system based on
Mamdani model were developed to evaluate the risk level of credit
applicants. A comparative analysis of the performances of both systems was
carried out and experimental results show that neural network with an
overall prediction accuracy of 96.89% performed better than the fuzzy logic
method with 94.44%. Finding from this study could provide useful information
on how to improve the performance of existing credit risk evaluation
systems.

To obtain a copy of the entire article, click on the link below.
www.igi-global.com/article/comparative-analysis-of-neural-network-and-fuzzy-
logic-techniques-in-credit-risk-evaluation/145777

To read a PDF sample of this article, click on the link below.
www.igi-global.com/viewtitlesample.aspx?id=145777
<http://www.igi-global.com/viewtitlesample.aspx?id=145777> 

ARTICLE 4

Open Fuzzy Synchronized Petri Net: Formal Specification Model for
Multi-agent Systems

Sofia Kouah (MISC Laboratory, University of Abdelhamid Mehri - Constantine,
Constantine, Algeria & Oum El Bouaghi, Algeria), Djamel Eddine Saïdouni
(MISC Laboratory, University of Abdelhamid Mehri – Constantine 2,
Constantine, Algeria), Ilham Kitouni (MISC Laboratory, University of
Abdelhamid Mehri – Constantine 2, Constantine, Algeria)

Designing Multi agent systems needs a high-level specification model which
supports abstraction, dynamicity, openness and enables fuzziness. Since the
model of Synchronized Petri Nets supports dynamicity and abstraction, we
extend it by fuzziness, openness and interaction with environment. The
proposed model called Open Fuzzy Synchronized Petri Nets (OFSyPN for short)
associates action name with transitions and enables openness feature and
interaction with environment. Each action has an uncertainty degree and
places are typed. The authors give an operational semantics for OFSyPN in
terms of Fuzzy Labeled Transition System (FLTS for short). FLTS is a
semantics model, which allows a concise action refinement representation and
deals with incomplete information through its fuzziness representation.
Furthermore the structure can be used to produce a tree of potential
concurrent design trajectories, named fuzzy labeled transition refinement
tree (FLTRT for short). We exemplify the OFSyPN model thought a case study.

To obtain a copy of the entire article, click on the link below.
www.igi-global.com/article/open-fuzzy-synchronized-petri-net/145778
<http://www.igi-global.com/article/open-fuzzy-synchronized-petri-net/145778>


To read a PDF sample of this article, click on the link below.
www.igi-global.com/viewtitlesample.aspx?id=145778
<http://www.igi-global.com/viewtitlesample.aspx?id=145778> 

  _____  

For full copies of the above articles, check for this issue of the
International Journal of Intelligent Information Technologies (IJIIT) in
your institution's library. This journal is also included in the IGI Global
aggregated "InfoSci-Journals" database: www.igi-global.com/isj
<http://www.igi-global.com/e-resources/infosci-databases/infosci-journals/>
.

  _____  

CALL FOR PAPERS

Mission of IJIIT:

The advent of the World Wide Web has sparked renewed interest in the area of
intelligent information technologies. There is a growing interest in
developing intelligent technologies that enable users to accomplish complex
tasks in web-centric environments with relative ease, utilizing such
technologies as intelligent agents, distributed computing in heterogeneous
environments, and computer supported collaborative work. The mission of the
International Journal of Intelligent Information Technologies (IJIIT) is to
bring together researchers in related fields such as information systems,
distributed AI, intelligent agents, and collaborative work, to explore and
discuss various aspects of design and development of intelligent
technologies. This journal provides a forum for academics and practitioners
to explore research issues related to not only the design, implementation
and deployment of intelligent systems and technologies, but also economic
issues and organizational impact. Papers related to all aspects of
intelligent systems including theoretical work on agent and multi-agent
systems as well as case studies offering insights into agent-based problem
solving with empirical or simulation based evidence are welcome.

Indices of IJIIT:

*	ACM Digital Library
*	Australian Business Deans Council (ABDC)
*	Bacon's Media Directory
*	Burrelle's Media Directory
*	Cabell's Directories
*	Compendex (Elsevier Engineering Index)
*	CSA Illumina
*	DBLP
*	DEST Register of Refereed Journals
*	Gale Directory of Publications & Broadcast Media
*	GetCited
*	Google Scholar
*	INSPEC
*	JournalTOCs
*	Library & Information Science Abstracts (LISA)
*	MediaFinder
*	Norwegian Social Science Data Services (NSD)
*	SCOPUS
*	The Index of Information Systems Journals
*	The Standard Periodical Directory
*	Thomson Reuters
*	Ulrich's Periodicals Directory
*	Web of Science

Coverage of IJIIT:

The International Journal of Intelligent Information Technologies (IJIIT)
encourages quality research dealing with (but not limited to) the following
topics: 

*  Agent-based auction, contracting, negotiation, and ecommerce 

*  Agent-based control and supply chain 

*  Agent-based simulation and application integration 

*  Cooperative and collaborative systems 

*  Distributed intelligent systems and technologies 

*  Human-agent interaction and experimental evaluation 

*  Implementation, deployment, diffusion, and organizational impact 

*  Integrating business intelligence from internal and external sources 

*  Intelligent agent and multi-agent systems in various domains 

*  Intelligent decision support systems 

*  Intelligent information retrieval and business intelligence 

*  Intelligent information systems development using design science
principles 

*  Intelligent Web mining and knowledge discovery systems 

*  Manufacturing information systems 

*  Models, architectures and behavior models for agent-oriented information
systems 

*  Multimedia information processing 

*  Privacy, security, and trust issues 

*  Reasoning, learning and adaptive systems 

*  Semantic Web, Web services, and ontologies

Interested authors should consult the journal's manuscript submission
guidelines
www.igi-global.com/calls-for-papers/international-journal-intelligent-inform
ation-technologies/1089
<http://www.igi-global.com/calls-for-papers/international-journal-intelligen
t-information-technologies/1089> 

 

=========================================

Vijayan Sugumaran, Ph.D.

Professor of Management Information Systems

Chair, Department of Decision and Information Sciences

School of Business Administration

Oakland University

Rochester, MI 48309

Phone: 248-370-4649

Fax: 248-370-4275

Email: sugumara at oakland.edu <mailto:sugumara at oakland.edu> 

=========================================