Both planning and design of municipal solid waste management systems (MSWMS) require accurate prediction of waste generation (WG). In this study, the hybrid of wavelet transform-adaptive neuro-fuzzy ...inference system (WT-ANFIS) and wavelet transform-artificial neural network (WT-ANN) is used to predict the weekly WG in Tehran, concerning complexity and dynamic MSWMS. In order to input variables preprocessing is done by WT and then new variables entered to ANFIS and ANN models. Consequently, output uncertainty of WT-ANFIS and WT-ANN models is done. The results achieved in this research indicate the positive effect of input variables preprocessing by WT in the prediction of weekly WG in Tehran, and it has led to noticeable increase in the accuracy of two model calculations. However, WT-ANFIS model had better results than WT-ANN model, because of the smaller uncertainty than WT-ANN model.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Designing and implementing biodiversity-based value chains can be a complex undertaking, especially in places where outcomes are uncertain and risks of project failure and cost overruns are high. We ...used the Stochastic Impact Evaluation (SIE) approach to guide the Intergovernmental Authority on Development (IGAD) on viable investment options in honey value chains, which the agency considered implementing as an economic incentive for communities along the Kenya-Somalia border to conserve biodiversity. The SIE approach allows for holistic analysis of project cost, benefit, and risk variables, including those with uncertain and missing information. It also identifies areas that pose critical uncertainties in the project. We started by conducting a baseline survey in Witu and Awer in Lamu County, Kenya. The aim of the survey was to establish the current farm income from beekeeping as a baseline, against which the prospective impacts of intervention options could be measured. We then developed an intervention decision model that was populated with all cost, benefit and risk variables relevant to beekeeping. After receiving training in making quantitative estimates, four subject-matter experts expressed their uncertainty about the proposed variables in the model by specifying probability distributions for them. We then used Monte Carlo simulation to project decision outcomes. We also identified variables that projected decision outcomes were most sensitive to, and we determined the value of information for each variable. The variable with the highest information value to the decision-maker in Witu was the honey price. In Awer, no additional information on any of the variables would change the recommendation to invest in honey value chains in the region. The analysis demonstrates a novel and comprehensive approach to decision-making for different stakeholders in a project where decision outcomes are uncertain.Introduction
An inexact rough-interval fuzzy linear programming (IRFLP) method is developed for agricultural irrigation systems to generate conjunctive water allocation strategies. The concept of “rough interval” ...is introduced in the modeling framework to represent dual-uncertain parameters. After the modeling formulation, an agricultural water allocation management system is provided to demonstrate the applicability of the developed method. The results show that reasonable solutions and allocation strategies are obtained. Based on the analysis of alternatives obtained from different scenarios, the significant impact of dual uncertainties existing in the system is specified. Comparisons between the results from IRFLP and interval-valued fuzzy linear programming are also conducted. The obtained rough-interval solutions correspond to the management strategies under both normal and special system conditions, and thus more conveniences would be provided for decision makers. Compared to the previous modeling efforts, the proposed IRFLP shows uniqueness in addressing the interaction between dual intervals of highly uncertain parameters, as well as their joint impact on the system.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
With the aid of disturbance observer strategy, this article aims to investigate the disturbance rejection and stabilization problems for periodic piecewise time-varying systems that are subject to ...time-varying delays, parameter uncertainties, nonlinear perturbations and exogenous disturbances. To be more specific, the periodic piecewise time-varying systems are built by segmenting the fundamental period of periodic systems into a limited number of subintervals. Further, the disturbances engendered from an exogenous system are estimated by deploying the disturbance observer and subsequently, on the premise of disturbance that is esimated, a robust controller protocol is constructed for the considered system. Moreover, by bridging the time-varying periodic piecewise Lyapunov-Krasovskii functional with a matrix polynomial lemma, a set of adequate criteria is framed, which confirms the asymptotic stability of the system that is being addressed. Subsequently, on the premise of established criteria, the design of periodic piecewise gain matrices of devised controller and configured observer are presented. Eventually, the importance and potential of the presented theoretical concepts are evidenced through offering a numerical illustration with the simulation results.
Justice-trust relationship has been well acknowledged in the organizational behavior research so far. However, the existing research on justice-trust paid little attention to the process-dynamics of ...trust formation in the newcomer employees (Colquitt and Rodell in
Academy of Management Journal, 54
(6), 1183–1206, Colquitt and Rodell
2011
; Schoorman et al. in
Academy of Management Review, 32
(2), 344,354, Schoorman et al.
2007
). The present study intends to unfold the trust formation phenomena of the newcomer employees where organizational justice perception leads to trust through organizational trustworthiness. Interactions between the dimensions of organizational justice perception and trustworthiness towards trust are the focal point of the study. We further propose that a moderated mediation model explains the trust formation phenomena comprehensively. Findings suggests that supervisor referent interpersonal justice moderates the indirect relationship between organizational justice and trust. Procedural and interactional justice also have significant relationships with trust through all the three dimensions of trustworthiness. The results indicated a full mediation for procedural justice and a partial mediation for interactional justice. The findings have important theoretical implications for uncertainty management, and psychological contract fulfillment theory.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
We propose a suitable analytical framework to perform numerical analysis of problems arising in compressible fluid models with uncertain data. We discuss both weak and strong stochastic approach, ...where the former is based on the knowledge of the mere distribution (law) of the random data typical for the Monte-Carlo and related methods, while the latter assumes the data to be known as a random variable on a given probability space aiming at obtaining the associated solution in the same form. As an example of the strong approach, we discuss the stochastic collocation method based on a piecewise constant approximation of the random data.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
This paper discusses about improvement of Global Positioning System (GPS) receiver position accuracy based on elevation angle and position uncertainty parameters. Kalman Filter method is used to ...estimate the receiver position which by default provides position uncertainty along with error in position. To improve accuracy, the proposed method focuses on proper selection of satellites to be considered among the visible satellites to evaluate the receiver’s position accuracy. At a particular epoch the combination of satellites with high elevation angles results in better receiver position. The analysis has been carried out by considering different combinations of satellites with high elevation angles from a number of visible satellites at a particular epoch. The results of the proposed method are very promising for precise applications of GPS particularly in the civil aviation sector.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In this paper we structure, obtain and analyze results of an expert elicitation on the relationship between U. S. government Research & Development funding and the likelihood of achieving advances in ...cellulosic biofuel technologies. While there was disagreement among the experts on each of the technologies, the patterns of disagreement suggest several distinct strategies. Selective Thermal Processing appears to be the most promising path, with the main question being how much funding is required to achieve success. Thus, a staged investment in this path looks promising. With respect to gasification, there remains fundamental disagreement over whether success is possible even at higher funding levels. Thus, basic research into the viability of the path makes sense. The Hydrolysis path induced the widest range of responses from the experts, indicating there may be value in collecting more information on this technology.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
A spectral formalism has been developed for the “non-intrusive” analysis of parametric uncertainty in reacting-flow systems. In comparison to conventional Monte Carlo analysis, this method quantifies ...the extent, dependence, and propagation of uncertainty through the model system and allows the correlation of uncertainties in specific parameters to the resulting uncertainty in detailed flame structure. For the homogeneous ignition chemistry of a hydrogen oxidation mechanism in supercritical water, spectral projection enhances existing Monte Carlo methods, adding detailed sensitivity information to uncertainty analysis and relating uncertainty propagation to reaction chemistry. For 1-D premixed flame calculations, the method quantifies the effect of each uncertain parameter on total uncertainty and flame structure, and localizes the effects of specific parameters within the flame itself. In both 0-D and 1-D examples, it is clear that known empirical uncertainties in model parameters may result in large uncertainties in the final output. This has important consequences for the development and evaluation of combustion models. This spectral formalism may be extended to multidimensional systems and can be used to develop more efficient “intrusive” reformulations of the governing equations to build uncertainty analysis directly into reacting flow simulations.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Water resource system planning is complicated by uncertainty on the magnitude and direction of climate change. Therefore, developments such as new infrastructure or changed management rules that ...would work acceptably well under a diverse set of future conditions (i.e., robust solutions) are preferred. Robust multi-objective optimisation can help identify advantageous system designs which include existing infrastructure plus a selected subset of new interventions. The method evaluates options using simulated water resource performance metrics statistically aggregated to summarise performance over the climate scenario ensemble. In most cases such ‘robustness metrics’ are sensitive to scenarios under which the system performs poorly and so results may be strongly influenced by a minority of unfavorable climate scenarios. Understanding the influence of specific climate scenarios on robust optimised decision alternatives can help better interpret their results. We propose an automated multi-criteria design-under-uncertainty sensitivity analysis formulation that uses multi-objective evolutionary algorithms to reveal robust and efficient designs under different samples of a climate scenario ensemble. The method is applied to a reservoir management problem in the Rufiji River basin, Tanzania, which involves the second largest dam in Africa. We find that solutions optimised for robustness under alternative groups of climate scenarios exhibit important differences. This becomes particularly decision-relevant if analysts and/or decision-makers have differing confidence levels in the relevance of certain climate scenarios. The proposed approach motivates continued research on how climate model credibility should inform climate scenario selection because it demonstrates the influence scenario selection has on recommendations arising from robust optimisation design processes.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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