Uniform modeling of parameter dependent nonlinear systems

This paper addresses the problem of approximating parameter dependent nonlinear systems in a unified framework. This modeling has been presented for the first time in the form of parameter dependent piecewise affine systems. In this model, the matrices and vectors defining piecewise affine systems are affine functions of parameters. Modeling of the system is done based on distinct spaces of state and parameter, and the operating regions are partitioned into the sections that we call ’multiplied simplices’. It is proven that this method of partitioning leads to less complexity of the approximated model compared with the few existing methods for modeling of parameter dependent nonlinear systems. It is also proven that the approximation is continuous for continuous functions and can be arbitrarily close to the original one. Next, the approximation error is calculated for a special class of parameter dependent nonlinear systems. For this class of systems, by solving an optimization problem, the operating regions can be partitioned into the minimum number of hyper-rectangles such that the modeling error does not exceed a specified value. This modeling method can be the first step towards analyzing the parameter dependent nonlinear systems with a uniform method.     

Adaptive Periodic Noise Reduction in Digital Images Using Fuzzy Transform

Journal of Mathematical Imaging and Vision - Periodic noise degrades the image quality by overlaying similar patterns. This noise appears as peaks in the image spectrum. In this research, a method...     

A Multi-Criteria Group Decision Making Methodology Using Interval Type-2 Fuzzy Sets: Application to Water Resources Management

In this paper, a new fuzzy group decision-making methodology which determines and incorporates negotiation powers of decision makers is developed. The proposed method is based on a combination of interval type-2 fuzzy sets and a multi-criteria decision making (MCDM) model, namely TOPSIS. To examine the applicability of the proposed methodology, it is used for finding the best scenario of allocating water and reclaimed wastewater to domestic, agricultural, and industrial water sectors and restoring groundwater quantity and quality in the Varamin region located in Tehran metropolitan area in Iran. The results show that the selected scenario leads to an acceptable groundwater conservation level during a long-term planning horizon. Although the capital cost of this scenario is high, which leads to groundwater restoration during the 34-year planning horizon, it is determined as the best allocation scenario. This scenario also entails the second least pumping cost, due to less water allocation from the groundwater. To evaluate the results of the proposed methodology, they are compared with those obtained using some well-known interval type-2 decision-making approaches including arithmetic-based, TOPSIS-based, and likelihood-based comparison methods. The Spearman correlation coefficient shows that the obtained results generally concur with those of the other methods. It is also concluded that the proposed methodology gives more reasonable results by calculating and considering the negotiation powers of decision makers in an extended TOPSIS-based group decision-making model.

     

Spatiotemporal modelling of urban quality of life (UQoL) using satellite images and GIS

ABSTRACT

In modern cities, life is primarily formed in interaction with various environmental, social, economic, infrastructural, hygienic, safety, political and cultural conditions. Urban quality of life (UQoL) is the result of such interactions. In general, both objective and subjective approaches are used in the study and modelling of UQoL. So far the studies have been conducted in forms of social and large-scale geographical studies mainly ignoring spatial differences of quality of life (QoL) in complicated urban environments. Moreover, QoL as one of the attributes of geographical environment is a dynamic and variable concept which has received little attention. Spatiotemporal modelling of this concept can contribute to monitoring the UQoL and planning for its improvement. The current study aims to develop a method for spatiotemporal modelling of UQoL. For this purpose, multi criteria decision making (MCDM) method and fuzzy logic are used. Moreover, given the variability of some indicators, temporal modelling of UQoL was conducted based on snapshot method in seasonal scale. In order to evaluate the proposed procedure, modelling of QoL was done at urban blocks scale in regions 3, 6, and 11 of Tehran, Iran. The results show the existence of a fairly regular pattern as an increase in desirability of UQoL from south to north of the area. The seasonal changes of UQoL show the improvement of environmental condition in spring and autumn compared to winter and summer. The result of sensitivity analysis shows the reliability of the modelling results. Since the effect of inputs on the fuzzy gamma output (2.5%) are less than the corresponding amount in VIKOR-fuzzy method (48%), it can be concluded that the output of fuzzy-gamma is more reliable.     

Application of cubic equation of state models in prediction of vapor–liquid equilibria for binary polyvinyl acetate/solvent solutions

The cubic equation of state (CEoS) is a powerful method for calculation of (vapor + liquid) equilibrium (VLE) in polymer solutions. Using CEoS for both the vapor and liquid phases allows one to calculate the non‐ideality of polymer solutions based on a single EoS approach. In this research, vapor–liquid equilibria calculations of polyvinyl acetate (PVAc)/solvent solutions were performed. In this approach, eight models containing PRSV and SRK CEoS separately combined with four mixing rules namely vdW1, vdW2, Wong–Sandler (WS), and Zhong–Masuoka (ZM) were applied to calculations of bubble point pressure. For the better prediction, the adjustable binary interaction parameters existing in any mixing rule were optimized. The results were very acceptable and satisfactory. Absolute average deviations (%AAD) between predicted results and experimental bubble point pressure data were calculated and presented. The capability of two cubic equations of state had a good agreement with experimental data and predict the correct type of phase behavior in all cases, but the performance of the PRSV + vdW2 was more reliable than the other models with 2.65% in AAD for total of solution systems. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40651.     

Optimal Inter-Basin Water Allocation Using Crisp and Fuzzy Shapley Games

In recent years, uneven distribution of available water resources as well as increasing water demands and overexploiting the water resources have brought severe need for transferring water from basins having sufficient water to basins facing water shortages. Therefore, optimal allocation of shared water resources in water transfer projects, considering the utilities of different stakeholders, physical limitations of the system and socioeconomic criteria is an important task. In this paper, a new methodology based on crisp and fuzzy Shapley games is developed for optimal allocation of inter-basin water resources. In the proposed methodology, initial water allocations are obtained using an optimization model considering an equity criterion. In the second step, the stakeholders form crisp coalitions to increase the total net benefit of the system as well as their own benefits and a crisp Shapley Value game is used to reallocate the benefits produced in the crisp coalitions. Lastly, to provide maximum total net benefit, fuzzy coalitions are constituted and the participation rates of water users to fuzzy coalitions are optimized. Then, the total net benefit is reallocated to water users in a rational and equitable way using Fuzzy Shapley Value game. The effectiveness of this method is examined by applying it to a large scale case study of water transfer from the Karoon river basin in southern Iran to the Rafsanjan plain in central Iran.     

A multi-product multi-period inventory control problem under inflation and discount: a parameter-tuned particle swarm optimization algorithm

In this paper, a seasonal multi-product multi-period inventory control problem is modeled in which the inventory costs are obtained under inflation and all-unit discount policy. Furthermore, the products are delivered in boxes of known number of items, and in case of shortage, a fraction of demand is considered backorder and a fraction lost sale. Besides, the total storage space and total available budget are limited. The objective is to find the optimal number of boxes of the products in different periods to minimize the total inventory cost (including ordering, holding, shortage, and purchasing costs). Since the integer nonlinear model of the problem is hard to solve using exact methods, a particle swarm optimization (PSO) algorithm is proposed to find a near-optimal solution. Since there is no bench mark available in the literature to justify and validate the results, a genetic algorithm is presented as well. In order to compare the performances of the two algorithms in terms of the fitness function and the required CPU time, they are first tuned using the Taguchi approach, in which a metric called “smaller is better” is used to model the response variable. Then, some numerical examples are provided to demonstrate the application and to validate the results obtained. The results show that, while both algorithms have statistically similar performances, PSO tends to be the better algorithm in almost all problems.     

The effects of ginger intake on weight loss and metabolic profiles among overweight and obese subjects: A systematic review and meta-analysis of randomized controlled trials

This systematic review and meta-analysis of randomized controlled trials (RCTs) was performed to summarize the effect of ginger intake on weight loss, glycemic control and lipid profiles among overweight and obese subjects. We searched the following databases through November 2017: MEDLINE, EMBASE, Web of Science, and Cochrane Central Register of Controlled Trials. The relevant data were extracted and assessed for quality of the studies according to the Cochrane risk of bias tool. Data were pooled using the inverse variance method and expressed as Standardized Mean Difference (SMD) with 95% Confidence Intervals (95% CI). Heterogeneity between studies was assessed by the Cochran Q statistic and I-squared tests (I²). Overall, 14 studies were included in the meta-analyses. Fourteen RCTs with 473 subjects were included in our meta-analysis. The results indicated that the supplementation with ginger significantly decreased body weight (BW) (SMD ?0.66; 95% CI, ?1.31, ?0.01; P = 0.04), waist-to-hip ratio (WHR) (SMD ?0.49; 95% CI, ?0.82, ?0.17; P = 0.003), hip ratio (HR) (SMD ?0.42; 95% CI, ?0.77, ?0.08; P = 0.01), fasting glucose (SMD ?0.68; 95% CI, ?1.23, ?0.05; P = 0.03) and insulin resistance index (HOMA-IR) (SMD ?1.67; 95% CI, ?2.86, ?0.48; P = 0.006), and significantly increased HDL-cholesterol levels (SMD 0.40; 95% CI, 0.10, 0.70; P = 0.009). We found no detrimental effect of ginger on body mass index (BMI) (SMD ?0.65; 95% CI, ?1.36, 0.06; P = 0.074), insulin (SMD ?0.54; 95% CI, ?1.43, 0.35; P = 0.23), triglycerides (SMD ?0.27; 95% CI, ?0.71, 0.18; P = 0.24), total- (SMD ?0.20; 95% CI, ?0.58, 0.18; P = 0.30) and LDL-cholesterol (SMD ?0.13; 95% CI, ?0.51, 0.24; P = 0.48). Overall, the current meta-analysis demonstrated that ginger intake reduced BW, WHR, HR, fasting glucose and HOMA-IR, and increased HDL-cholesterol, but did not affect insulin, BMI, triglycerides, total- and LDL-cholesterol levels.