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Article
Publication date: 11 May 2010

V.P. Sakthivel, R. Bhuvaneswari and S. Subramanian

The purpose of this paper is to present the application of an adaptive bacterial foraging (BF) algorithm for the design optimization of an energy efficient induction motor.

429

Abstract

Purpose

The purpose of this paper is to present the application of an adaptive bacterial foraging (BF) algorithm for the design optimization of an energy efficient induction motor.

Design/methodology/approach

The induction motor design problem is formulated as a mixed integer nonlinear optimization problem. A set of nine independent variables is selected, and to make the machine feasible and practically acceptable, six constraints are imposed on the design. Two different objective functions are considered, namely, the annual active material cost, and the sum of the annual active material cost, annual cost of the active power loss of the motor and annual energy cost required to supply such power loss. A new adaptive BF algorithm is used for solving the optimization problem. A generic penalty function method, which does not require any penalty coefficient, is employed for constraint handling.

Findings

The adaptive BF algorithm is validated for two sample motors and benchmarked with the genetic algorithm, particle swarm optimization, simple BF algorithm, and conventional design methods. The results show that the proposed algorithm outperforms the other methods in both the solution quality and convergence rate. The annual cost of the induction motor is remarkably reduced when designed on the basis of minimizing its annual total cost, instead of minimizing its material cost only.

Originality/value

To the best of the knowledge, none of the existing work has applied the BF algorithms for electrical machine design problems. Therefore, the solution to this problem constitutes the main contribution of the paper. According to the huge number of induction motors operating all over the world, the BF techniques used in their design, on minimum annual cost basis, will lead to a tremendous saving in global energy consumption.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 29 no. 3
Type: Research Article
ISSN: 0332-1649

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Article
Publication date: 10 April 2007

S. Subramanian and R. Bhuvaneswari

This paper aims to employ particle swarm optimization (PSO) technique for optimum design of single‐phase induction motor (SPIM) on the basis of maximizing the efficiency of the…

732

Abstract

Purpose

This paper aims to employ particle swarm optimization (PSO) technique for optimum design of single‐phase induction motor (SPIM) on the basis of maximizing the efficiency of the motor simultaneously satisfying a set of performance constraints.

Design/methodology/approach

The design problem of a SPIM is presented as a nonlinear optimization problem on the basis of maximizing the efficiency of the motor. A set of performance constraints are imposed in the optimization procedure. Particle swarm optimization technique is used as an optimization tool for obtaining the motor dimensions corresponding to maximum efficiency. Incorporation of PSO as a derivative free optimization technique in solving SPIM optimum design problem significantly relieves the assumptions imposed on the optimized objective function.

Findings

This approach has been applied to two sample motors and the results are compared with the evolutionary programming (EP) results. It is observed that the proposed approach is effective and robust.

Originality/value

The fields of application of SPIMs are expanding day by day. The emphasis on energy conservation demands an improvement of the efficiency of single‐phase induction motors. Hence, the design optimization of these motors with efficiency as objective function assumes great importance.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 26 no. 2
Type: Research Article
ISSN: 0332-1649

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Article
Publication date: 13 November 2007

S. Padma, R. Bhuvaneswari and S. Subramanian

The purpose of this paper is to present a comparative study of the various soft computing techniques and their application to optimum design of three‐phase induction motor design.

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Abstract

Purpose

The purpose of this paper is to present a comparative study of the various soft computing techniques and their application to optimum design of three‐phase induction motor design.

Design/methodology/approach

The need for energy conservation is increasing the requirements for increased efficiency levels of induction motor. It is therefore important to optimize the efficiency of induction motor in order to obtain significant energy savings. To optimize the efficiency, design of the induction motor has to be chosen appropriately. In this paper, computational intelligence techniques such as artificial neural network, fuzzy logic, genetic algorithm, differential evolution, evolutionary programming, particle swarm optimization, simulated annealing approach, radial basis function, and hybrid approach are applied to solve the induction motor design optimization problem.

Findings

These methods are tested on two sample motors and the results are compared and validated against the conventional Modified Hooke‐Jeeves design results and the effectiveness of each proposed method has also been illustrated in detail.

Originality/value

This comparison will be highly useful for the design engineers in selecting the best method for obtaining the optimal dimensions of three‐phase induction motor.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 26 no. 5
Type: Research Article
ISSN: 0332-1649

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Book part
Publication date: 31 December 2010

Lan Wang, Ratoola Kundu and Xiangming Chen

The new town concept originated from the ideal city model of Ebenezer Howard and expanded from Europe to America in the 1900s. It has reemerged as a site for accommodating…

Abstract

The new town concept originated from the ideal city model of Ebenezer Howard and expanded from Europe to America in the 1900s. It has reemerged as a site for accommodating population from highly dense urban centers of China and India since the early twenty-first century. The massive infusion of public and private investments has enabled the emergence of new towns in China and India as planned centers of world-class residential, commercial, and work spaces. The rational goal of de-densifying the crowded central cities can lead to a more balanced distribution and use of resources across the metropolitan regions with more spacious housing for the growing middle class in China and India. Yet it is a relatively small number of the wealthy and mobile people who have turned out to be beneficiaries of the mostly high-end housing and well-developed transport infrastructure that evokes social and economic polarizations and political contestations. In this chapter, we will examine: (1) how these top-down planned and developed new towns have reshaped the urbanization process of the megacities in India and China, (2) the socio-spatial influence of these settlements on the central city as well as the surrounding rural areas, and (3) the expected and actual spatial users (both old and new residents) of the new towns? We address these questions by organizing two pairs of cases in a systematic framework: Anting New Town and Thames Town in Shanghai, China and Rajarhat New Town and the Kolkata West International City (KWIC) near Kolkata, India.

Details

Suburbanization in Global Society
Type: Book
ISBN: 978-0-85724-348-5

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Article
Publication date: 9 October 2019

Elham Ali Shammar and Ammar Thabit Zahary

Internet has changed radically in the way people interact in the virtual world, in their careers or social relationships. IoT technology has added a new vision to this process by…

7100

Abstract

Purpose

Internet has changed radically in the way people interact in the virtual world, in their careers or social relationships. IoT technology has added a new vision to this process by enabling connections between smart objects and humans, and also between smart objects themselves, which leads to anything, anytime, anywhere, and any media communications. IoT allows objects to physically see, hear, think, and perform tasks by making them talk to each other, share information and coordinate decisions. To enable the vision of IoT, it utilizes technologies such as ubiquitous computing, context awareness, RFID, WSN, embedded devices, CPS, communication technologies, and internet protocols. IoT is considered to be the future internet, which is significantly different from the Internet we use today. The purpose of this paper is to provide up-to-date literature on trends of IoT research which is driven by the need for convergence of several interdisciplinary technologies and new applications.

Design/methodology/approach

A comprehensive IoT literature review has been performed in this paper as a survey. The survey starts by providing an overview of IoT concepts, visions and evolutions. IoT architectures are also explored. Then, the most important components of IoT are discussed including a thorough discussion of IoT operating systems such as Tiny OS, Contiki OS, FreeRTOS, and RIOT. A review of IoT applications is also presented in this paper and finally, IoT challenges that can be recently encountered by researchers are introduced.

Findings

Studies of IoT literature and projects show the disproportionate importance of technology in IoT projects, which are often driven by technological interventions rather than innovation in the business model. There are a number of serious concerns about the dangers of IoT growth, particularly in the areas of privacy and security; hence, industry and government began addressing these concerns. At the end, what makes IoT exciting is that we do not yet know the exact use cases which would have the ability to significantly influence our lives.

Originality/value

This survey provides a comprehensive literature review on IoT techniques, operating systems and trends.

Details

Library Hi Tech, vol. 38 no. 1
Type: Research Article
ISSN: 0737-8831

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Article
Publication date: 1 December 2005

S. Subramanian and R. Bhuvaneswari

This paper presents a novel multiobjective optimal design of three phase induction motor using simulated annealing (SA) technique for minimizing annual material cost and annual…

524

Abstract

Purpose

This paper presents a novel multiobjective optimal design of three phase induction motor using simulated annealing (SA) technique for minimizing annual material cost and annual loss cost as two objectives.

Design/methodology/approach

The design problem of a three‐phase induction motor is presented as a nonlinear multicriterion optimization problem on the basis of minimizing the annual cost of the motor. The annual cost referred is the sum of the annual interest and depreciation of motor active material costs, annual cost of active power loss of the motor and the annual energy cost required to supply such power loss. A computer package is built which generates initial values of motor parameters and gives the optimal values of these parameters with more than one objective function and nonviolated constraints. The problem is solved by giving weights which reflect the priority of objective functions. The SA technique is used as a tool to solve the problem.

Findings

To verify the validity, the proposed method is applied to a three‐phase induction motor design. From the results, it is found that the proposed method is fast and efficient and hence it is useful for multiobjective design of an induction motor.

Originality/value

This method is particularly useful in satisfying the needs of motor producer and consumer by prioritizing their needs and finally arriving at a best compromise solution.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 24 no. 4
Type: Research Article
ISSN: 0332-1649

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Book part
Publication date: 30 September 2020

Hera Khan, Ayush Srivastav and Amit Kumar Mishra

A detailed description will be provided of all the classification algorithms that have been widely used in the domain of medical science. The foundation will be laid by giving a…

Abstract

A detailed description will be provided of all the classification algorithms that have been widely used in the domain of medical science. The foundation will be laid by giving a comprehensive overview pertaining to the background and history of the classification algorithms. This will be followed by an extensive discussion regarding various techniques of classification algorithm in machine learning (ML) hence concluding with their relevant applications in data analysis in medical science and health care. To begin with, the initials of this chapter will deal with the basic fundamentals required for a profound understanding of the classification techniques in ML which will comprise of the underlying differences between Unsupervised and Supervised Learning followed by the basic terminologies of classification and its history. Further, it will include the types of classification algorithms ranging from linear classifiers like Logistic Regression, Naïve Bayes to Nearest Neighbour, Support Vector Machine, Tree-based Classifiers, and Neural Networks, and their respective mathematics. Ensemble algorithms such as Majority Voting, Boosting, Bagging, Stacking will also be discussed at great length along with their relevant applications. Furthermore, this chapter will also incorporate comprehensive elucidation regarding the areas of application of such classification algorithms in the field of biomedicine and health care and their contribution to decision-making systems and predictive analysis. To conclude, this chapter will devote highly in the field of research and development as it will provide a thorough insight to the classification algorithms and their relevant applications used in the cases of the healthcare development sector.

Details

Big Data Analytics and Intelligence: A Perspective for Health Care
Type: Book
ISBN: 978-1-83909-099-8

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Article
Publication date: 1 October 2006

S. Subramanian and R. Bhuvaneswari

The power transformer is one of the most important pieces of equipment in a power system. The necessity for the optimum design of a power transformer arises because the design…

346

Abstract

Purpose

The power transformer is one of the most important pieces of equipment in a power system. The necessity for the optimum design of a power transformer arises because the design chosen should satisfy all the limitations and restrictions placed on it. This paper presents an improved fast evolutionary programming (IFEP) technique for the optimal design of a three‐phase power transformer.

Design/methodology/approach

The optimization of the transformer design problem is formulated as an NLP problem, expressing the objective and constraint functions in terms of the selected independent variables. Here the cost of the transformer is considered as the objective function and is the sum of material cost of stampings and copper windings, cost of cooling tube arrangements, cost of cooling medium, insulation cost and labour cost. A computer program is written from which the optimal design parameters are obtained. For optimization, the classical evolutionary programming (CEP) technique and its variant the IFEP technique are used and the results are compared.

Findings

The application of CEP and IFEP for transformer design has been demonstrated on two test cases. It has been observed that this IFEP outperforms the CEP in obtaining the optimum design of transformers of smaller as well as larger ratings in terms of execution time, convergence rate, quality and success rate.

Originality/value

The proposed method results in the economical design of a three‐phase power transformer which can significantly reduce the cost of manufacturing transformers.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 25 no. 4
Type: Research Article
ISSN: 0332-1649

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Book part
Publication date: 29 August 2022

Aaditeshwar Seth

Abstract

Details

Technology and (Dis)Empowerment: A Call to Technologists
Type: Book
ISBN: 978-1-80382-393-5

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Article
Publication date: 13 March 2017

Qianling Chen, Min Zhang and Xiande Zhao

Big data produced by mobile apps contains valuable knowledge about customers and markets and have been viewed as productive resources. The purpose of this paper is to propose a…

8710

Abstract

Purpose

Big data produced by mobile apps contains valuable knowledge about customers and markets and have been viewed as productive resources. The purpose of this paper is to propose a multiple methods approach to elicit intelligence and value from big data by analysing the customer behaviour in mobile app usage.

Design/methodology/approach

The big data analytical approach is developed using three data mining techniques: RFM(recency, frequency, monetary) analysis, link analysis, and association rule learning. The authors then conduct a case study to apply this approach to analyse the transaction data extracted from a mobile app.

Findings

This approach can identify high value and mass customers, and understand their patterns and preferences in using the functions of the mobile app. Such knowledge enables the developer to capture the behaviour of large pools of customers and to improve products and services by mixing and matching the functions and offering personalised promotions and marketing information.

Originality/value

The approach used in this study balances complexity with usability, thus facilitating corporate use of big data in making product improvement and customisation decisions. The approach allows developers to gain insights into customer behaviour and function usage preferences by analysing big data. The identified associations between functions can also help developers improve existing, and design new, products and services to satisfy customers’ unfulfilled requirements.

Details

Industrial Management & Data Systems, vol. 117 no. 2
Type: Research Article
ISSN: 0263-5577

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