Soft computing framework for intelligent human-machine system design, simulation and optimization

Zha, Xuan F.

doi:10.1007/s00500-002-0196-4

Cited by 10 publications

(9 citation statements)

References 24 publications

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“…Like the wine lovers, the wine interested were experienced wine drinkers, with 41% having 20+ years of wine drinking experience. This is consistent with the dominant age range: 45% are ages [45][46][47][48][49][50][51][52][53][54][55][56][57][58][59][60][61][62][63][64]. The other age ranges have roughly equal representation: 15% are 19-24; 16% are 25-34; and 10% are 65 and up. Most of the members of the wine interested category are travelling with a spouse (65%), but they are also the group most likely to be travelling with other family members.…”

Section: Wine Interested (52%)supporting

confidence: 87%

“…All these approaches are recognized as learning systems used iteratively and flexibly, drawing from philosophy, psychology, sociology, and organizational theory (Ossenbruggen, 1994). Several researchers have argued that the potential of various soft computing technologies is limited only by the imagination of their users (Negnevitsky, 2011;Ruan, 1997;Zha, 2003). However, there is no dearth of OR/MS practitioners who look down upon these soft approaches and advocate/practice less-pertinent hard optimization techniques even in highly subjective and uncertain problem domains .…”

Section: Soft Or/ms Paradigmmentioning

confidence: 99%

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Implications of limited investor attention to customer–supplier information transfers

Zhu

2014

The Quarterly Review of Economics and Finance

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We examine the (dis)incentive effects created by the respective tax systems to invest in human capital in Atlantic Canada and compare this to a select group of provinces from the rest of Canada. While findings show a steady decline in effective tax rates through the years, thereby creating an incentive effect to invest in post-secondary education, disproportionately higher rate gap differentials in the Atlantic Provinces, on average, combined with negative comparative statics reveal a somewhat different undertone. The counterproductive nature of the competing policies effectively nullifies any status quo argument for education or tax policy in the Atlantic Provinces, when compared to their brethren. The graduate retention rebate provides some solace to the narrative in helping to alleviate early tax burdens and equalize returns, but is difficult to claim effectiveness in assuaging any monetary windfall associated with migration. IntroductionThe goal of this paper is to assess the (dis)incentive effects created by the provincial tax systems for human capital investment in Atlantic Canada. Our test subjects are university graduates, but we note that such methodology could be applied to any level or subset of the population that possess human capital deemed scarce and productive, in the economic sense. We do not purport to suggest that university graduates are more important in the economic well being of an economy than, say, skilled trades or college graduates, e.g., and encourage one to think of our case as a subset of a larger sample of possibilities. Our presumption, like our goal, is simple; namely, an empirical investigation of incentivizing the tax system in Atlantic Canada remains an unexplored possibility for strategic policy implementation to retain and recruit scarce resources in the market for human capital. We use the impact on effective tax rates (ETRs) and rates of return as our policy litmus test and explore by empirical and simulation analysis the unilateral exploitation of a select number of provincial tax systems. Some may claim that this work puts the * Collins would like to acknowledge the support of the CRS-SSHRC institutional research grant at St. Francis Xavier University in helping to complete this research.proverbial cart before the horse, as it were, since to attract workers a province needs the requisite infrastructure and such may not be currently present at the appropriate level(s) to warrant an increase in the supply of skilled labour. To that end, we suggest that a more accurate assessment (or, at least, a plausible alternative) might be akin to a "chicken or the egg" argument; namely, which comes first? We leave this debate up to the interested reader for now, and focus on establishing the empirics of the analysis in an effort to add the requisite fodder for a more informed discussion.While previous research has examined the disincentive effects created by the tax system for, e.g., university and college graduates (see, for instance, Burbidge et al., 2012), the current study is diff...

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Section: Wine Interested (52%)supporting

confidence: 87%

Section: Soft Or/ms Paradigmmentioning

confidence: 99%

Implications of limited investor attention to customer–supplier information transfers

Zhu

2014

The Quarterly Review of Economics and Finance

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“…Soft computing enables solutions to be obtained for problems that have not been able to be solved satisfactorily by hard computing methods [25] [26]. Typically FL has been used to implement applications that are based on a recommendation task.…”

Section: B Soft Computing Techniquesmentioning

confidence: 99%

Categorisation of Customer and Advisor in Contact Centres

Shah¹,

Roy²,

Tiwari³

et al. 2007

IJCIR

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This paper reports on the findings of a research project that had the objective to build a decision support system to categorise customer and service advisor (CSA) within customer contact centre (CCC) environment. We provide the methodology to develop a fuzzy expert system which assigns a new customer or advisor to the pre-defined categories. Categorising of customer and service advisor based on behavioural, demographic and experience variables, was one of the core objectives of the study. In the paper the process of building such a model which categorise customer and advisor through soft computing techniques is described. The behavioural aspects of customer and advisor are not an exhaustive list; but the authors own findings from the case studies at the contact centres. The reported findings and results are very promising, making the proposed model a useful tool in the decision making process, while some of the discussed problems and limitations are of interest to researchers who intend to use soft computing based approaches in other similar real life problems. The framework allows the managers within contact centres to understand the behavioural segments of customers and advisors (CSA) working at the centre and to provide information which would enable them to deliver better customer satisfaction.

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“…ANN is a mathematical model for predicting system performance (i.e., system output) inspired by the structure and function of human biological neural networks. ANNs have been studied extensively and applied in various problems [1] and [2]. Their benefits have not yet been fully realized in the context of human-posture models because there are many variations of ANNs, and selecting the appropriate form and associated parameters for a particular application can often be more of an art than a science.…”

Section: Introductionmentioning

confidence: 99%

Artificial Neural Network-Based Prediction of Human Posture

Bataineh

Marler

Abdel‐Malek

2013

Digital Human Modeling and Applications in Health, Safety, Ergonomics, and Risk Management. Human Body Modeling and Ergonomics

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Abstract. The use of an artificial neural network (ANN) in many practical complicated problems encourages its implementation in the digital human modeling (DHM) world. DHM problems are complicated and need powerful tools like ANN to provide acceptable solutions. Human posture prediction is a DHM field that has been studied thoroughly in recent years. This work focuses on using a general regression neural network (GRNN) for human posture prediction. This type of ANN has advantages over others when incorporated in DHM problems like posture prediction. A new heuristic approach is also presented in this study to determine the GRNN parameters that lead to the best performance and prediction capability. The results are promising: a high success rate is obtained for predicting 41 outputs, which represent the upperbody degrees of freedom of a human model. This work initiates future focus on embedding GRNN to generalize human posture prediction in a task-based manner.

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Soft computing framework for intelligent human-machine system design, simulation and optimization

Cited by 10 publications

References 24 publications

Implications of limited investor attention to customer–supplier information transfers

Implications of limited investor attention to customer–supplier information transfers

Categorisation of Customer and Advisor in Contact Centres

Artificial Neural Network-Based Prediction of Human Posture

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