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Article
Publication date: 19 May 2022

Laxmi Gupta and Ravi Shankar

Battery integration with renewable energy and conventional power grid is common practice in smart grid systems and provides higher operational flexibility. Abundant issues and…

Abstract

Purpose

Battery integration with renewable energy and conventional power grid is common practice in smart grid systems and provides higher operational flexibility. Abundant issues and challenges to the Indian smart grid while integrating renewable energy and storage technology will give timely emphasis to grasp uninterrupted power supply in forthcoming trend. Hence, this paper aims to acknowledge different barriers of battery integration and evaluate them to develop approaches for restricting their influence.

Design/methodology/approach

A multi-model approach is used to illustrate how these challenges are interrelated by systematically handling expert views and helps to chronologically assemble various issues from the greatest severe to the slightest severe ones. Further, these barriers are grouped using the cross-impact matrix multiplication applied to the classification analysis (MICMAC) study grounded on their driving and dependence power. Also, hypothesis testing was done to validate the obtained model.

Findings

It provides a complete thoughtful on directional interrelationships between the barriers and delivers the best possible solution for the active operation of the smart grid and its performance.

Research limitations/implications

There is a significant requirement for high-tech inventions outside the transmission grid to function for the integration of renewables and storage systems.

Practical implications

The model will support policymakers in building knowledgeable decisions while chronologically rejecting the challenges of battery integration in smart grid systems to improve power grid performance.

Originality/value

Based on author’s best knowledge, there is hardly any research that explicitly explains the framework for the barriers of battery integration in grid for developing countries like India. It is one of the first attempts to understand the fundamental barriers for battery integration. This study adds significantly to the literature on the energy sector by capturing the perspective of various stakeholders.

Article
Publication date: 25 September 2007

Gianfranco Minati

The purpose of this paper is to describe fundamental concepts and theoretical challenges with regard to systems, and to build on these in proposing new theoretical frameworks…

1675

Abstract

Purpose

The purpose of this paper is to describe fundamental concepts and theoretical challenges with regard to systems, and to build on these in proposing new theoretical frameworks relevant to learning, for example in so‐called learning organizations.

Design/methodology/approach

The paper focuses on some crucial fundamental aspects introduced in the literature in order to establish a general rather than generic usage of the systems concept. Issues of definition and theoretical frameworks are clarified before introducing new theoretical challenges for Systems Thinking, such as the perspective of a General Theory of Emergence (GTE), new modelling approaches and new concepts including Multiple Systems (MSs) and Collective Beings (CBs).

Findings

New approaches for modelling management and corporate learning are described. The paper also explains the Dynamical Usage of Models (DYSAM) developed to deal with MSs and CBs for managing learning systems able to self‐design evolutionary strategies.

Originality/value

The paper expands understanding of the notion of system and underlines the relevance of systems thinking in modelling and facilitating corporate learning.

Details

The Learning Organization, vol. 14 no. 6
Type: Research Article
ISSN: 0969-6474

Keywords

Article
Publication date: 23 August 2011

Raja Ben Mohamed, Hichem Ben Nasr and Faouzi M'Sahli

The purpose of this paper is to present a new concept based on a neural network validity approach in the area of multimodel for complex systems.

Abstract

Purpose

The purpose of this paper is to present a new concept based on a neural network validity approach in the area of multimodel for complex systems.

Design/methodology/approach

The multimodel approach was recently developed in order to solve the modeling problems and the control of complex systems. The strategy of this approach coincides with the usual approach of the engineer which consists in subdividing a complex problem to a set of simple, manageable sub‐problems that can be solved separately. However, this approach still faces some problems in design, especially in determining models and in finding the appropriate method of calculating validities.

Findings

A novel approach based on neural network validity shows very remarkable performances in multimodel for complex systems.

Research limitations/implications

The validity of each model is based on the convergence of each neural network. For a fast convergence the proposed approach can be online to give a good performance in multimodel representation for system with rapid dynamics.

Practical implications

The proposed concept discussed in the paper has the potential to be applied to complex systems.

Originality/value

The suggested approach is implemented and reviewed with a complex dynamic and fast process compared to the residue approach commonly used in the calculation of validities. The results prove to be satisfactory and show a good accuracy.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 4 no. 3
Type: Research Article
ISSN: 1756-378X

Keywords

Article
Publication date: 5 September 2016

Emre Cevikcan

Walking-worker assembly lines can be regarded as an effective method to achieve the above-mentioned characteristics. In such systems, workers, following each other, travel…

Abstract

Purpose

Walking-worker assembly lines can be regarded as an effective method to achieve the above-mentioned characteristics. In such systems, workers, following each other, travel workstations in sequence by performing all of the required tasks of their own product. As the eventual stage of assembly line design, efforts should be made for capacity adjustments to meet the demand in terms of allocating tasks to workers via assembly line balancing. In this context, the purpose of this study is to address the balancing problem for multi-model walking-worker assembly systems, with the aim of improving planning capability for such systems by means of developing an optimization methodology.

Design/methodology/approach

Two linear integer programming models are proposed to balance a multi-model walking-worker assembly line optimally in a sequential manner. The first mathematical programming model attempts to determine number of workers in each segment (i.e. rabbit chase loop) for each model. The second model generates stations in each segment to smooth workflow. What is more, heuristic algorithms are provided due to computational burden of mathematical programming models. Two segment generation heuristic algorithms and a station generation heuristic algorithm are provided for the addressed problem.

Findings

The application of the mathematical programming approach improved the performance of a tap-off box assembly line in terms of number of workers (9.1 per cent) and non-value-added time ratio (between 27.9 and 26.1 per cent for different models) when compared to a classical assembly system design. In addition, the proposed approach (i.e. segmented walking-worker assembly line) provided a more convenient working environment (28.1 and 40.8 per cent shorter walking distance for different models) in contrast with the overall walking-worker assembly line. Meanwhile, segment generation heuristics yielded reduction in labour requirement for a considerable number (43.7 and 49.1 per cent) of test problems. Finally, gaps between the objective values and the lower bounds have been observed as 8.3 per cent (Segment Generation Heuristic 1) and 6.1 (Segment Generation Heuristic 2).

Practical implications

The proposed study presents a decision support for walking-worker line balancing with high level of solution quality and computational performance for even large-sized assembly systems. That being the case, it contributes to the management of real-life assembly systems in terms of labour planning and ergonomics. Owing to the fact that the methodology has the potential of reducing labour requirement, it will present the opportunity of utilizing freed-up capacity for new lines in the start-up period or other bottleneck processes. In addition, this study offers a working environment where skill of the workers can be improved within reasonable walking distances.

Originality/value

To the best knowledge of the author, workload balancing on multi-model walking-worker assembly lines with rabbit chase loop(s) has not yet been handled. Addressing this research gap, this paper presents a methodology including mathematical programming models and heuristic algorithms to solve the multi-model walking-worker assembly line balancing problem for the first time.

Details

Assembly Automation, vol. 36 no. 4
Type: Research Article
ISSN: 0144-5154

Keywords

Article
Publication date: 5 March 2018

Stéphane Vivier

This paper aims to introduce an original application of the corrected response surface method (CRSM) in the context of the optimal design of a permanent magnet synchronous machine…

Abstract

Purpose

This paper aims to introduce an original application of the corrected response surface method (CRSM) in the context of the optimal design of a permanent magnet synchronous machine used as an integrated starter generator. This method makes it possible to carry out this design in a very efficient manner, in comparison with conventional optimization approaches.

Design/methodology/approach

The search for optimal conditions is achieved by the joint use of two multi-physics models of the machine to be optimized. The former models most finely the physical functioning of the machine; it is called “fine model”. The second model describes the same physical phenomena as the fine model but must be much quicker to evaluate. Thus, to minimize its evaluation time, it is necessary to simplify it considerably. It is called “coarse model”. The lightness of the coarse model allows it to be used intensively by conventional optimization algorithms. On the other hand, the fine reference model makes it possible to recalibrate the results obtained from the coarse model at any instant, and mainly at the end of each classical optimization. The difference in definition between fine and coarse models implies that these two models do not give the same output values for the same input configuration. The approach described in this study proposes to correct the values of the coarse model outputs by constructing an adjustment (correcting) response surface. This gives the name to this method. It then becomes possible to have the entire load of the optimization carried over to the coarse model adjusted by the addition of this correction response surface.

Findings

The application of this method shows satisfactory results, in particular in comparison with those obtained with a traditional optimization approach based on a single (fine) model. It thus appears that the approach by CRSM makes it possible to converge much more quickly toward the optimal configurations. Also, the use of response surfaces for optimization makes it possible to capitalize the modeling data, thus making it possible to reuse them, if necessary, for subsequent optimal design studies. Numerous tests show that this approach is relatively robust to the variations of many important functioning parameters.

Originality/value

The CRSM technique is an indirect multi-model optimization method. This paper presents the application of this relatively undeveloped optimization approach, combining the features and benefits of (Indirect) efficient global optimization techniques and (multi-model) space mapping methods.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 37 no. 2
Type: Research Article
ISSN: 0332-1649

Keywords

Article
Publication date: 18 September 2023

Xiao-Yu Xu, Syed Muhammad Usman Tayyab, Qingdan Jia and Albert H. Huang

Video game streaming (VGS) is emerging as an extremely popular, highly interactive, inordinately subscribed and very dynamic form of digital media. Incorporated environmental…

Abstract

Purpose

Video game streaming (VGS) is emerging as an extremely popular, highly interactive, inordinately subscribed and very dynamic form of digital media. Incorporated environmental elements, gratifications and user pre-existing attitudes in VGS, this paper presents the development of an extended model of uses and gratification theory (EUGT) for predicting users' behavior in novel technological context.

Design/methodology/approach

The proposed model was empirically tested in VGS context due to its popularity, interactivity and relevance. Data collected from 308 VGS users and structural equation modeling (SEM) was employed to assess the hypotheses. Multi-model comparison technique was used to assess the explanatory power of EUGT.

Findings

The findings confirmed three significant types elements in determining VGS viewers' engagement, including gratifications (e.g. involvement), environmental cues (e.g. medium appeal) and user predispositions (e.g. pre-existing attitudes). The results revealed that emerging technologies provide potential opportunities for new motives and gratifications, and highlighted the significant of pre-existing attitudes as a mediator in the gratification-uses link.

Originality/value

This study is one of its kind in tackling the criticism on UGT of considering media users too rational or active. The study achieved this objective by considering environmental impacts on user behavior which is largely ignored in recent UGT studies. Also, by incorporating users pre-existing attitudes into UGT framework, this study conceptualized and empirically verified the higher explanatory power of EUGT through a novel multi-modal approach in VGS. Compared to other rival models, EUGS provides a more robust explanation of users' behavior. The findings contribute to the literature of UGT, VGS and users' engagement.

Details

Information Technology & People, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0959-3845

Keywords

Article
Publication date: 7 March 2016

Stephan Körner and Frank Holzäpfel

Wake vortices that are generated by an aircraft as a consequence of lift constitute a potential danger to the following aircraft. To predict and avoid dangerous situations, wake…

Abstract

Purpose

Wake vortices that are generated by an aircraft as a consequence of lift constitute a potential danger to the following aircraft. To predict and avoid dangerous situations, wake vortex transport and decay models have been developed. Being based on different model physics, they can complement each other with their individual strengths. This paper investigates the skill of a Multi-Model Ensemble (MME) approach to improve prediction performance. Therefore, this paper aims to use wake vortex models developed by NASA (APA3.2, APA3.4, TDP2.1) and by DLR (P2P). Furthermore, this paper analyzes the possibility to use the ensemble spread to compute uncertainty envelopes.

Design/methodology/approach

An MME approach called Reliability Ensemble Averaging (REA) is adapted and used to the wake vortex predictions. To train the ensemble, a set of wake vortex measurements accomplished at the airports of Frankfurt (WakeFRA), Munich (WakeMUC) and at a special airport Oberpfaffenhofen was applied.

Findings

The REA approach can outperform the best member of the ensemble, on average, regarding the root-mean-square error. Moreover, the ensemble delivers reasonable uncertainty envelopes.

Practical implications

Reliable wake vortex predictions may be applicable for both tactical optimization of aircraft separation at airports and airborne wake vortex prediction and avoidance.

Originality/value

Ensemble approaches are widely used in weather forecasting, but they have never been applied to wake vortex predictions. Until today, the uncertainty envelopes for wake vortex forecasts have been computed among others from perturbed initial conditions or perturbed physics as well as from uncertainties from environmental conditions or from safety margins but not from the spread of structurally independent model forecasts.

Details

Aircraft Engineering and Aerospace Technology: An International Journal, vol. 88 no. 2
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 5 February 2018

Olugbenga Wilson Adejo and Thomas Connolly

The purpose of this paper is to empirically investigate and compare the use of multiple data sources, different classifiers and ensembles of classifiers technique in predicting…

1184

Abstract

Purpose

The purpose of this paper is to empirically investigate and compare the use of multiple data sources, different classifiers and ensembles of classifiers technique in predicting student academic performance. The study will compare the performance and efficiency of ensemble techniques that make use of different combination of data sources with that of base classifiers with single data source.

Design/methodology/approach

Using a quantitative research methodology, data samples of 141 learners enrolled in the University of the West of Scotland were extracted from the institution’s databases and also collected through survey questionnaire. The research focused on three data sources: student record system, learning management system and survey, and also used three state-of-art data mining classifiers, namely, decision tree, artificial neural network and support vector machine for the modeling. In addition, the ensembles of these base classifiers were used in the student performance prediction and the performances of the seven different models developed were compared using six different evaluation metrics.

Findings

The results show that the approach of using multiple data sources along with heterogeneous ensemble techniques is very efficient and accurate in prediction of student performance as well as help in proper identification of student at risk of attrition.

Practical implications

The approach proposed in this study will help the educational administrators and policy makers working within educational sector in the development of new policies and curriculum on higher education that are relevant to student retention. In addition, the general implications of this research to practice is its ability to accurately help in early identification of students at risk of dropping out of HE from the combination of data sources so that necessary support and intervention can be provided.

Originality/value

The research empirically investigated and compared the performance accuracy and efficiency of single classifiers and ensemble of classifiers that make use of single and multiple data sources. The study has developed a novel hybrid model that can be used for predicting student performance that is high in accuracy and efficient in performance. Generally, this research study advances the understanding of the application of ensemble techniques to predicting student performance using learner data and has successfully addressed these fundamental questions: What combination of variables will accurately predict student academic performance? What is the potential of the use of stacking ensemble techniques in accurately predicting student academic performance?

Details

Journal of Applied Research in Higher Education, vol. 10 no. 1
Type: Research Article
ISSN: 2050-7003

Keywords

Content available
Article
Publication date: 1 November 2011

Graeme Hutcheson

985

Abstract

Details

Journal of Modelling in Management, vol. 6 no. 3
Type: Research Article
ISSN: 1746-5664

Article
Publication date: 1 March 2022

Ken-Yien Leong, Mohamed Ariff, Zarei Alireza and M. Ishaq Bhatti

The objective of this paper is to investigate the validity of stock valuation theories and their forecasting ability by conducting an empirical study. It employs four most…

Abstract

Purpose

The objective of this paper is to investigate the validity of stock valuation theories and their forecasting ability by conducting an empirical study. It employs four most commonly used theories which are then tested using 19-year banking-firm market data. The usefulness of these models demonstrates with promising results.

Design/methodology/approach

This paper conducts a multi-country study using the multi-model testing approach to evaluate validity of theories and forecast accuracy of banking firms. It employs four methodology models used in finance literature; (1) P/E multiples model, (2) accounting-information-based clean surplus model, (3) theoretical model based on Gordon and Shapiro (1956) method and (4) the Damodaran-Kottler Free Cash Flow or FCF theory based on discounting model.

Findings

The tests show that the four theories under tests have a significant fit with actual price formation. The explained variation ranges from 72 to 92%, so the explanatory power of the theories accounting for variations in bank prices over 19-year period is substantial. The models fit suggest that the P/E model has superior predictive power followed by the RIM, DDM and FCFE. These findings shed new lights on the relative performance of valuation models.

Research limitations/implications

The study is limited in terms of the sample period size for 1999–2019. The availability of essential financial data prior to 2000 is very limited, so one can understand interpretation of statistical results under certain assumptions.

Practical implications

The paper suggests that one-factor model is better than the two-factor model.

Originality/value

The work done in this paper is unpublished and original contribution to banking and finance literature and also not under consideration for publication in any other journal.

Details

International Journal of Managerial Finance, vol. 19 no. 2
Type: Research Article
ISSN: 1743-9132

Keywords

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