Ghosh soumya (68 Ergebnisse)

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Paperback. Zustand: Brand New. 2013 edition. 100 pages. 8.75x6.00x0.25 inches. In Stock.

Paperback. Zustand: Brand New. 102 pages. 9.00x6.00x0.25 inches. In Stock.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The present study has attempted to apply the advantage of neuro-genetic algorithms for optimal decision making in maximum utilization of natural resources. Hydro-power is one of the inexpensive, but a reliable source of alternative energy which is foreseen as the possible answer to the present crisis in the energy sector. However, the major problem related to hydro-energy is its dependency on location. An ideal location can produce maximum energy with minimum loss. Besides, such power-plant also requires substantial amount of land which is a precious resource nowadays due to the rapid and uncontrolled urbanization observed in most of the urban centres in the World. The feasibility of such plants also depends on social acceptance as well as the level of environmental casualty and economic benefit, all of which is also spatially dependent. Decision making algorithms are applied to identify better solution if a problem has more than one alternative explication. Nature based algorithms are found to be efficient enough to catalyze such kind of decision making analysis. That is why the present study tries to utilize nature based algorithms to solve the problems of location selection for hydropower plants. The study employed six different types of nature based algorithms to select one of the locations among many available for installation of hydropower plant in the North Eastern part of the Indian subcontinent. The locations are selected based on their in stream resources and included in the decision making as alternatives. A methodology of criteria selection, determination of weightage and applications of bioinspired algorithms are adopted to produce utmost exertion of the available natural resources with minimum hostility and wastage of the same.…

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book proposes complex hierarchical deep architectures (HDA) for predicting bankruptcy, a topical issue for business and corporate institutions that in the past has been tackled using statistical, market-based and machine-intelligence prediction models. The HDA are formed through fuzzy rough tensor deep staking networks (FRTDSN) with structured, hierarchical rough Bayesian (HRB) models. FRTDSN is formalized through TDSN and fuzzy rough sets, and HRB is formed by incorporating probabilistic rough sets in structured hierarchical Bayesian model. Then FRTDSN is integrated with HRB to form the compound FRTDSN-HRB model. HRB enhances the prediction accuracy of FRTDSN-HRB model. The experimental datasets are adopted from Korean construction companies and American and European non-financial companies, and the research presented focuses on the impact of choice of cut-off points, sampling procedures and business cycle on the accuracy of bankruptcy prediction models. The bookalso highlights the fact that misclassification can result in erroneous predictions leading to prohibitive costs to investors and the economy, and shows that choice of cut-off point and sampling procedures affect rankings of various models. It also suggests that empirical cut-off points estimated from training samples result in the lowest misclassification costs for all the models. The book confirms that FRTDSN-HRB achieves superior performance compared to other statistical and soft-computing models. The experimental results are given in terms of several important statistical parameters revolving different business cycles and sub-cycles for the datasets considered and are of immense benefit to researchers working in this area.…

paperback. Zustand: Sehr gut. 176 Seiten; 9783030277512.2 Gewicht in Gramm: 1.

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Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | The present study has attempted to apply the advantage of neuro-genetic algorithms for optimal decision making in maximum utilization of natural resources. Hydro-power is one of the inexpensive, but a reliable source of alternative energy which is foreseen as the possible answer to the present crisis in the energy sector. However, the major problem related to hydro-energy is its dependency on location. An ideal location can produce maximum energy with minimum loss. Besides, such power-plant also requires substantial amount of land which is a precious resource nowadays due to the rapid and uncontrolled urbanization observed in most of the urban centres in the World. The feasibility of such plants also depends on social acceptance as well as the level of environmental casualty and economic benefit, all of which is also spatially dependent. Decision making algorithms are applied to identify better solution if a problem has more than one alternative explication. Nature based algorithms are found to be efficient enough to catalyze such kind of decision making analysis. That is why the present study tries to utilize nature based algorithms to solve the problems of location selection for hydropower plants. The study employed six different types of nature based algorithms to select one of the locations among many available for installation of hydropower plant in the North Eastern part of the Indian subcontinent. The locations are selected based on their in stream resources and included in the decision making as alternatives. A methodology of criteria selection, determination of weightage and applications of bioinspired algorithms are adopted to produce utmost exertion of the available natural resources with minimum hostility and wastage of the same.…

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book offers a comprehensive guide to the modelling of operational risk using possibility theory. It provides a set of methods for measuring operational risks under a certain degree of vagueness and impreciseness, as encountered in real-life data. It shows how possibility theory and indeterminate uncertainty-encompassing degrees of belief can be applied in analysing the risk function, and describes the parametric g-and-h distribution associated with extreme value theory as an interesting candidate in this regard. The book offers a complete assessment of fuzzy methods for determining both value at risk (VaR) and subjective value at risk (SVaR), together with a stability estimation of VaR and SVaR. Based on the simulation studies and case studies reported on here, the possibilistic quantification of risk performs consistently better than the probabilistic model. Risk is evaluated by integrating two fuzzy techniques: the fuzzy analytic hierarchy process and the fuzzy extension of techniques for order preference by similarity to the ideal solution. Because of its specialized content, it is primarily intended for postgraduates and researchers with a basic knowledge of algebra and calculus, and can be used as reference guide for research-level courses on fuzzy sets, possibility theory and mathematical finance. The book also offers a useful source of information for banking and finance professionals investigating different risk-related aspects.…

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book offers a comprehensive guide to the modelling of operational risk using possibility theory. It provides a set of methods for measuring operational risks under a certain degree of vagueness and impreciseness, as encountered in real-life data. It shows how possibility theory and indeterminate uncertainty-encompassing degrees of belief can be applied in analysing the risk function, and describes the parametric g-and-h distribution associated with extreme value theory as an interesting candidate in this regard. The book offers a complete assessment of fuzzy methods for determining both value at risk (VaR) and subjective value at risk (SVaR), together with a stability estimation of VaR and SVaR. Based on the simulation studies and case studies reported on here, the possibilistic quantification of risk performs consistently better than the probabilistic model. Risk is evaluated by integrating two fuzzy techniques: the fuzzy analytic hierarchy process and the fuzzy extension of techniques for order preference by similarity to the ideal solution. Because of its specialized content, it is primarily intended for postgraduates and researchers with a basic knowledge of algebra and calculus, and can be used as reference guide for research-level courses on fuzzy sets, possibility theory and mathematical finance. The book also offers a useful source of information for banking and finance professionals investigating different risk-related aspects.…

Paperback. Zustand: Brand New. 156 pages. 9.25x6.10x0.51 inches. In Stock.

Hardcover. Zustand: Brand New. 152 pages. 9.25x6.10x0.70 inches. In Stock.

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Hardcover. Zustand: Brand New. 208 pages. 9.25x6.25x0.75 inches. In Stock.

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