-------- Weitergeleitete Nachricht -------- Betreff: [AISWorld] Contents of International Journal of Intelligent Information Technologies (IJIIT) - Vol. 12, No. 1 Datum: Tue, 16 Feb 2016 10:44:42 -0500 Von: Vijayan Sugumaran sugumara@oakland.edu An: aisworld@lists.aisnet.org

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

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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/ .

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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

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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@oakland.edu mailto:sugumara@oakland.edu

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