[AISWorld] Contents of IJIIT 13(4) - International Journal of Intelligent Information Technologies (IJIIT)

Vijayan Sugumaran sugumara at oakland.edu
Tue Aug 1 10:11:18 EDT 2017

The contents of the latest issue of:
International Journal of Intelligent Information Technologies (IJIIT)
Volume 13, Issue 4, October - December 2017
Indexed by: Compendex (Elsevier Engineering Index), INSPEC, SCOPUS, Web of
Science Emerging Sources Citation Index (ESCI)
For a complete list of indexing and abstracting services that include this
journal, please reference the bottom of this announcement.
Published: Quarterly in Print and Electronically
ISSN: 1548-3657; EISSN: 1548-3665; 
Published by IGI Global Publishing, Hershey, USA

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

Note: The International Journal of Intelligent Information Technologies
(IJIIT) has an Open Access option, which allows individuals and institutions
unrestricted access to its published content. Unlike traditional
subscription-based publishing models, open access content is available
without having to purchase or subscribe to the journal in which the content
is published. All IGI Global manuscripts are accepted based on a
double-blind peer review editorial process.


Special Issue on Intelligent Sensing for Big Data

Zheng Xu (The Ministry of Public Security, The Third Research Institute,
Shanghai, China), Yunhuai Liu (Jingyuan Peking University, Beijing Institute
of Big Data, Beijing, China), Raymond Kim-Kwang Choo (The University of
Texas at San Antonio, San Antonio, TX, USA), Neil Y. Yen (University of
Aizu, Aizuwakamatsu, Japan)

To obtain a copy of the Guest Editorial Preface, click on the link below.
&ptid=158255&ctid=15&t=Special Issue on Intelligent Sensing for Big Data


Aggregation Operators of Trapezoidal Intuitionistic Fuzzy Sets to
Multicriteria Decision Making

Jufeng Ye (Zhejiang Tongji Vocational College of Science and Technology,
Xiaoshan, China)

This paper presents the trapezoidal intuitionistic fuzzy weighted averaging
(TIFWA) operator, trapezoidal intuitionistic fuzzy ordered weighted
averaging (TIFOWA) operator, trapezoidal intuitionistic fuzzy weighted
geometric (TIFWG) operator, and trapezoidal intuitionistic fuzzy ordered
weighted geometric (TIFOWG) operator to aggregate the trapezoidal
intuitionistic fuzzy information and investigates their properties.
Furthermore, a multicriteria decision making method based on the TIFOWA and
TIFOWG operators and the score function and accuracy function of a
trapezoidal intuitionistic fuzzy number is established to deal with the
multicriteria decision making problem with trapezoidal intuitionistic fuzzy
information. Finally, an illustrative example demonstrates the application
of the proposed method.

To obtain a copy of the entire article, click on the link below.

To read a PDF sample of this article, click on the link below.


Multicriteria Decision-Making Method Under a Single Valued Neutrosophic

Shapu Ren (Shaoxing University, Department of Electrical and Information
Engineering, Shaoxing, China)

A single valued neutrosophic set (SVNS) is a subclass of neutrosophic sets,
which generalizes fuzzy sets, interval valued fuzzy set, and intuitionistic
fuzzy set. It can be used to easily express incomplete, indeterminate and
inconsistent information. This paper introduces the Dice similarity measure
of single valued neutrosophic numbers (SVNNs) for ranking SVNNs and a single
valued neutrosophic prioritized weighted geometric (SVNPWG) operator for
aggregating single valued neutrosophic information. Based on the SVNPWG
operator and the Dice similarity measure for SVNNs, a multicriteria
decision-making method with different priority levels in the criteria is
established in which the evaluation values of alternatives with respective
to criteria are represented in the form of SVNNs. The ranking order of
alternatives is performed through the Dice measure and the best one(s) can
be determined as well. Finally, an illustrative example shows the
application of the proposed method.

To obtain a copy of the entire article, click on the link below.

To read a PDF sample of this article, click on the link below.


Designing Extreme Learning Machine Network Structure Based on Tolerance
Rough Set

Han Ke (North China University of Water Resources and Electric Power,
Zhengzhou, China)

In this paper, we present a new extreme learning machine network structure
on the basis of tolerance rough set. The purpose of this paper is to realize
the high-efficiency and multi-dimensional ELM network structure. Various
published algorithms have been applied to breast cancer datasets, but rough
set is a fairly new intelligent technique that applies to predict breast
cancer recurrence. We analyze Ljubljana Breast Cancer Dataset, firstly,
obtain lower and upper approximations and calculate the accuracy and quality
of the classification. The high values of the quality of classification and
accuracy prove that the attributes selected can well approximate the
classification. Rough sets approach is established to solve the prolem of

To obtain a copy of the entire article, click on the link below.

To read a PDF sample of this article, click on the link below.


Coordination and Optimization of Large Equipment Complete Service in Cloud
Based Manufacturing

Xiaochun Sheng (Jiangsu University of Technology, School of Computer
Engineering, Changzhou, China), Kefeng Wang (Jiangsu University of
Technology, School of Computer Engineering, Changzhou, China)

The paper studies the cloud manufacturing service platform and mode in the
coordination and optimization of large equipment complete service (LECS). A
set of theory based system of coordination and optimization is
systematically established to support and implement LECS' cloud
manufacturing mode. The research results show that the collaborative logic
framework proposed is of macro guidance significance; the composite synergy
mechanism system designed realizes all-round cooperative target; the
collaborative optimization model and algorithm established have validity and
practicality through instance verification. It systematically realizes the
collaborative management of resource choice and optimizing configuration,
the plan and control in the process of service, and so on. It can ensure the
stability of manufacturing resource service seamless, green, environmental
protection, and high quality. It achieves optimization of the overall system
coordination. The study also provides a theoretical basis and scientific
method for large equipment enterprise from manufacturer to a service
integrator transformation.

To obtain a copy of the entire article, click on the link below.

To read a PDF sample of this article, click on the link below.


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



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
*	DEST Register of Refereed Journals
*	Gale Directory of Publications & Broadcast Media
*	GetCited
*	Google Scholar
*	JournalTOCs
*	Library & Information Science Abstracts (LISA)
*	MediaFinder
*	Norwegian Social Science Data Services (NSD)
*	The Index of Information Systems Journals
*	The Standard Periodical Directory
*	Ulrich's Periodicals Directory
*	Web of Science
*	Web of Science Emerging Sources Citation Index (ESCI)

Coverage of IJIIT:

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

*  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

*  Intelligent Web mining and knowledge discovery systems 

*  Manufacturing information systems 

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

*  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


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