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Article
Publication date: 7 October 2019

Implementation of a Web interface for hybrid intelligent systems: A comparison study of two hybrid intelligent systems

Shinji Sakamoto, Admir Barolli, Leonard Barolli and Shusuke Okamoto

The purpose of this paper is to implement a Web interface for hybrid intelligent systems. Using the implemented Web interface, this paper evaluates two hybrid intelligent…

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Abstract

Purpose

The purpose of this paper is to implement a Web interface for hybrid intelligent systems. Using the implemented Web interface, this paper evaluates two hybrid intelligent systems based on particle swarm optimization, hill climbing and distributed genetic algorithm to solve the node placement problem in wireless mesh networks (WMNs).

Design/methodology/approach

The node placement problem in WMNs is well-known to be a computationally hard problem. Therefore, the authors use intelligent algorithms to solve this problem. The implemented systems are intelligent systems based on meta-heuristics algorithms: Particle Swarm Optimization (PSO), Hill Climbing (HC) and Distributed Genetic Algorithm (DGA). The authors implement two hybrid intelligent systems: WMN-PSODGA and WMN-PSOHC-DGA.

Findings

The authors carried out simulations using the implemented Web interface. From the simulations results, it was found that the WMN-PSOHC-DGA system has a better performance compared with the WMN-PSODGA system.

Research limitations/implications

For simulations, the authors considered Normal distribution of mesh clients. In the future, the authors need to consider different client distributions, patterns, number of mesh nodes and communication distance.

Originality/value

In this research work, the authors implemented a Web interface for hybrid intelligent systems. The implemented interface can be extended for other metaheuristic algorithms.

Details

International Journal of Web Information Systems, vol. 15 no. 4
Type: Research Article
DOI: https://doi.org/10.1108/IJWIS-10-2018-0071
ISSN: 1744-0084

Keywords

  • Particle swarm optimization
  • Distributed genetic algorithm
  • Hill climbing
  • Hybrid intelligent system
  • Web interface
  • Wireless mesh networks

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Article
Publication date: 3 August 2015

The hybrid intelligent systems design using grey systems theory

Scarlat Emil and Virginia Mărăcine

The purpose of this paper is to discuss how tacit and explicit knowledge determine grey knowledge and how these are stimulated through interactions within networks…

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Abstract

Purpose

The purpose of this paper is to discuss how tacit and explicit knowledge determine grey knowledge and how these are stimulated through interactions within networks, forming the grey hybrid intelligent systems (HISs). The feedback processes and mechanisms between internal and external knowledge determine the apparition of grey knowledge into an intelligent system (IS). The extension of ISs is determined by the ubiquity of the internet but, in our framework, the grey knowledge flows assure the viability and effectiveness of these systems.

Design/methodology/approach

Some characteristics of the Hybrid Intelligent Knowledge Systems are put forward along with a series of models of hybrid computational intelligence architectures. More, relevant examples from the literature related to the hybrid systems architectures are presented, underlying their main advantages and disadvantages.

Findings

Due to the lack of a common framework it remains often difficult to compare the various HISs conceptually and evaluate their performance comparatively. Different applications in different areas are needed for establishing the best combinations between models that are designed using grey, fuzzy, neural network, genetic, evolutionist and other methods. But all these systems are knowledge dependent, the main flow that is used in all parts of every kind of system being the knowledge. Grey knowledge is an important part of the real systems and the study of its proprieties using the methods and techniques of grey system theory remains an important direction of the researches.

Originality/value

The paper discusses the differences among the three types of knowledge and how they and the grey systems theory can be used in different hybrid architectures.

Details

Grey Systems: Theory and Application, vol. 5 no. 2
Type: Research Article
DOI: https://doi.org/10.1108/GS-05-2015-0022
ISSN: 2043-9377

Keywords

  • Artificial intelligence
  • Grey knowledge
  • Grey systems theory
  • Hybrid models
  • Explicit knowledge
  • Intelligent knowledge systems

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Article
Publication date: 31 August 2004

Using a virtual student model for testing intelligent tutoring systems

Mircea Gh. Negoita and David Pritchard

Education is increasingly using Intelligent Tutoring Systems (ITS), both for modelling instructional and teaching strategies and for enhancing educational programs. The…

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Abstract

Education is increasingly using Intelligent Tutoring Systems (ITS), both for modelling instructional and teaching strategies and for enhancing educational programs. The first part of the paper introduces the basic structure of an ITS as well as common problems being experienced within the ITS community. The second part describes WITNeSS ‐ an original hybrid intelligent system using Fuzzy‐Neural‐GA techniques for optimising the presentation of learning material to a student. The original work in this paper is related to the concept of a “virtual student”. This student model, modelled using fuzzy technologies, will be useful for any ITS, providing it with an optimal learning strategy for fitting the ITS itself to the unique needs of each individual student. In the third part, experiments focus on problems developing a “virtual student” model, which simulates, in a rudimentary way, human learning behaviour. Part four finishes with concluding remarks.

Details

Interactive Technology and Smart Education, vol. 1 no. 3
Type: Research Article
DOI: https://doi.org/10.1108/17415650480000023
ISSN: 1741-5659

Keywords

  • Intelligent Tutoring Systems
  • hybrid intelligent systems
  • fuzzy systems
  • neural networks
  • Intelligent learning systems

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Article
Publication date: 11 November 2013

Developing a hybrid intelligent model for constructing a size recommendation expert system in textile industries

Jamal Shahrabi, Esmaeil Hadavandi and Maryam Salehi Esfandarani

In shopping, for selecting the appropriate garments, people have to try on multiple garments. This problem is due to lack of a sizing system based on updated…

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Abstract

Purpose

In shopping, for selecting the appropriate garments, people have to try on multiple garments. This problem is due to lack of a sizing system based on updated anthropometric data and the classification system that introduces the appropriate size from the sizing chart to each person. To solve this problem, as a first study in the literature, a hybrid intelligent classification model as a size recommendation expert system is proposed. The paper aims to discuss these issues.

Design/methodology/approach

Three stages for developing a hybrid intelligent classification system based on data clustering and probabilistic neural network (PNN) are proposed. In the first stage, the clustering algorithm is used for specifying the sizing chart. In the second stage, the resulting sizing chart is used as a reference for developing a new intelligent classification system by using a PNN. At the last stage, the accuracy of the proposed model is evaluated by using the Iranian male's body type data set.

Findings

Experimental results show that the proposed model has a good accuracy and can be used as a size recommendation expert system to specify the right size for the customers. By using the proposed model and designing an interface for it, a decision support system was developed as a size recommendation expert system that was used by an apparel sales store. The results were time saving and more satisfying for the customers by selecting the appropriate apparel size for them.

Originality/value

In this paper, as a first study in literature, a hybrid intelligent model for developing a size recommendation expert system based on data clustering and a PNN to enable the salesperson to help the consumer in choosing the right size is proposed. In the first stage, the clustering algorithm is used for specifying the sizing chart. In the second stage, the resulting sizing chart is used as a reference to develop a new intelligent classification system by using a PNN. In the last stage, the accuracy of the proposed model is evaluated by using testing data. The proposed model achieved an 87.2 percent accuracy rate that is very promising.

Details

International Journal of Clothing Science and Technology, vol. 25 no. 5
Type: Research Article
DOI: https://doi.org/10.1108/IJCST-04-2012-0015
ISSN: 0955-6222

Keywords

  • Cluster analysis
  • Hybrid intelligent system
  • Probabilistic neural network
  • Size recommendation system
  • Sizing system

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Article
Publication date: 1 April 1999

A framework for a hybrid intelligent system in support of marketing strategy development

Shuliang Li, Yanqing Duan, Russell Kinman and John S. Edwards

A framework for a hybrid intelligent support system is proposed, on the basis of a discussion of the main problems of current computer‐based support systems and the roles…

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Abstract

A framework for a hybrid intelligent support system is proposed, on the basis of a discussion of the main problems of current computer‐based support systems and the roles for computer‐based systems in developing marketing strategy. The objectives of the framework are: to integrate the strengths of different support techniques and technologies; to assist strategic analysis; to couple strategic analysis with managers’ judgement; to help managers deal with uncertainty; and to aid strategic thinking. Within this framework, the benefits of different strategic analysis models are combined to offer enhanced support for a logical sequence of strategic analysis, while the advantages of diverse support techniques and technologies are integrated and fitted to support different aspects of the marketing strategy development process. As well as the theoretical basis for the proposed framework, the paper also examines the associated technical issues.

Details

Marketing Intelligence & Planning, vol. 17 no. 2
Type: Research Article
DOI: https://doi.org/10.1108/02634509910260922
ISSN: 0263-4503

Keywords

  • Information technology
  • Marketing information systems
  • Marketing management
  • Marketing strategy

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Article
Publication date: 1 August 1999

The application of intelligent hybrid techniques for the mass appraisal of residential properties

William McCluskey and Sarabjot Anand

Hybrid systems as the next generation of intelligent applications within the field of mass appraisal and valuation are investigated. Motivated by the obvious limitations…

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Abstract

Hybrid systems as the next generation of intelligent applications within the field of mass appraisal and valuation are investigated. Motivated by the obvious limitations of paradigms that are being used in isolation or as stand‐alone techniques such as multiple regression analysis, artificial neural networks and expert systems. Clearly, there are distinct advantages in integrating two or more information processing systems that would address some of the discrete problems of individual techniques. Examines first, the strategic development of mass appraisal approaches which have traditionally been based on “stand‐alone” techniques; second, the potential application of an intelligent hybrid system. Highlights possible solutions by investigating various hybrid systems that may be developed incorporating a nearest neighbour algorithm (k‐NN). The enhancements are aimed at two major deficiencies in traditional distance metrics; user dependence for attribute weights and biases in the distance metric towards matching categorical variables in the retrieval of neighbours. Solutions include statistical techniques: mean, coefficient of variation and significant mean. Data mining paradigms based on a loosely coupled neural network or alternatively a tight coupling with genetic algorithms are used to discover attribute weights. The hybrid architectures developed are applied to a property data set and their performance measured based on their predictive value as well as perspicuity. Concludes by considering the application and the relevance of these techniques within the field of computer assisted mass appraisal.

Details

Journal of Property Investment & Finance, vol. 17 no. 3
Type: Research Article
DOI: https://doi.org/10.1108/14635789910270495
ISSN: 1463-578X

Keywords

  • Appraisals
  • Data mining
  • Expert systems
  • Neural networks
  • Valuation

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Article
Publication date: 8 April 2019

Approach to establish a hybrid intelligent model for crack diagnosis in a fix-hinge beam structure

Sanjay Kumar Behera, Dayal R. Parhi and Harish C. Das

With the development of research toward damage detection in structural elements, the use of artificial intelligent methods for crack detection plays a vital role in…

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Abstract

Purpose

With the development of research toward damage detection in structural elements, the use of artificial intelligent methods for crack detection plays a vital role in solving the crack-related problems. The purpose of this paper is to establish a methodology that can detect and analyze crack development in a beam structure subjected to transverse free vibration.

Design/methodology/approach

Hybrid intelligent systems have acquired their own distinction as a potential problem-solving methodology adopted by researchers and scientists. It can be applied in many areas like science, technology, business and commerce. There have been the efforts by researchers in the recent past to combine the individual artificial intelligent techniques in parallel to generate optimal solutions for the problems. So it is an innovative effort to develop a strong computationally intelligent hybrid system based on different combinations of available artificial intelligence (AI) techniques.

Findings

In the present research, an integration of different AI techniques has been tested for accuracy. Theoretical, numerical and experimental investigations have been carried out using a fix-hinge aluminum beam of specified dimension in the presence and absence of cracks. The paper also gives an insight into the comparison of relative crack locations and crack depths obtained from numerical and experimental results with that of the results of the hybrid intelligent model and found to be in good agreement.

Originality/value

The paper covers the work to verify the accuracy of hybrid controllers in a fix-hinge beam which is very rare to find in the available literature. To overcome the limitations of standalone AI techniques, a hybrid methodology has been adopted. The output results for crack location and crack depth have been compared with experimental results, and the deviation of results is found to be within the satisfactory limit.

Details

International Journal of Structural Integrity, vol. 10 no. 2
Type: Research Article
DOI: https://doi.org/10.1108/IJSI-05-2018-0029
ISSN: 1757-9864

Keywords

  • Natural frequency
  • Crack
  • Hybrid

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Article
Publication date: 1 June 2000

Developing marketing strategy with MarStra: the support system and the real‐world tests

Shuliang Li

Explores the potential of a hybrid intelligent system in supporting marketing strategy development. First, a hybrid intelligent system for developing marketing strategy…

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Abstract

Explores the potential of a hybrid intelligent system in supporting marketing strategy development. First, a hybrid intelligent system for developing marketing strategy, called MarStra (developed by the author), is outlined. Then discusses the real‐world tests of MarStra with marketing directors in five large UK companies. Empirical evidence from the companies involved indicates that MarStra is very helpful and useful in: providing strategic analysis guidance; coupling strategic analysis with managerial judgement; helping strategic thinking; dealing with fuzziness and uncertainty; and supporting group assessment of strategic marketing factors. The intelligent outputs generated by MarStra were reported to be surprisingly accurate, mostly sound and useful prompts.

Details

Marketing Intelligence & Planning, vol. 18 no. 3
Type: Research Article
DOI: https://doi.org/10.1108/02634500010327926
ISSN: 0263-4503

Keywords

  • Marketing strategy
  • Fuzzy logic
  • Expert systems
  • Decision‐support systems
  • Hybrid systems

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Article
Publication date: 1 April 2001

GloStra – a hybrid system for developing global strategy and associated Internet strategy

Shuliang Li and Barry J. Davies

An intelligent hybrid system, called GloStra (developed by the author), for developing global marketing strategy and associated Internet marketing strategy is reported in…

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Abstract

An intelligent hybrid system, called GloStra (developed by the author), for developing global marketing strategy and associated Internet marketing strategy is reported in this paper. The hybrid system is built to integrate the strengths of expert systems, fuzzy logic, artificial neural networks and decision support technology; and to link the development of global marketing strategy with the formulation of associated Internet marketing strategy. In the paper, the system architecture, the functional modules of the hybrid system and other associated technical issues are addressed. The directions for further research in this field are also highlighted.

Details

Industrial Management & Data Systems, vol. 101 no. 3
Type: Research Article
DOI: https://doi.org/10.1108/02635570110386643
ISSN: 0263-5577

Keywords

  • Global marketing
  • Marketing strategy
  • Marketing planning
  • Hybrid systems
  • Expert systems
  • Information systems

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Article
Publication date: 2 October 2020

Hybrid intelligent vehicle system for managing construction supply chain in precast concrete building construction projects

Zul-Atfi Bin Ismail

While the adversarial nature of precast concrete (PC) building construction is frequently cited in the PC building construction press, only a few researchers have…

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Abstract

Purpose

While the adversarial nature of precast concrete (PC) building construction is frequently cited in the PC building construction press, only a few researchers have investigated construction supply chain management within the construction industry. Due to the interdisciplinary transportation environment, which inevitably results in disruption, the uses of construction supply chain and recovery from construction supply chain risk must be a subject of real interest, yet transportation management research in this area is scarce.

Design/methodology/approach

The purpose of this study is to discuss the weakness in system approaches and their application for managing precast concrete building in the context of construction supply chain practice and how to overcome it. As a precursor to this paper, the paper reviews current construction supply chain management occurrence on PC building construction and explores the hybrid intelligent vehicle tools and techniques currently being used on such management. This paper also presents the new hybrid intelligent vehicle-based approach to manage construction supply chain risk and reduce associated tension on PC building construction schemes.

Findings

The findings reveal the need for more sophisticated construction supply chain management solutions which accord with the needs of PC building construction schemes.

Originality/value

The paper concludes by presenting a research framework for developing such a system in the future.

Details

World Journal of Engineering, vol. ahead-of-print no. ahead-of-print
Type: Research Article
DOI: https://doi.org/10.1108/WJE-08-2020-0361
ISSN: 1708-5284

Keywords

  • PC building
  • Construction
  • Risk
  • Supply chain management
  • Hybrid intelligent vehicle
  • Precast concrete

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