
 The spectral ratio between horizontal and vertical components (H/V ratio) of microtremors measured at the ground surface has been used to estimate fundamental periods and amplification factors of a site, although this technique lacks theoretical background. The aim of this article is to formulate the H/V technique in terms of the characteristics of Rayleigh and Love waves, and to contribute to improve the technique. The improvement includes use of not only peaks but also troughs in the H/V ratio for reliable estimation of the period and use of a newly proposed smoothing function for better estimation of the amplification factor. The formulation leads to a simple formula for the amplification factor expressed with the H/V ratio. With microtremor data measured at 546 junior high schools in 23 wards of Tokyo, the improved technique is applied to mapping site periods and amplification factors in the area.

Ground Motion Characteristics Estimated from Spectral Ratio between Horizontal and Verticcl Components of Mietremors.

Spectral analysis is a practical technology used for rapid analysis of fruit maturity. Least-squares support vector regression (LSSVR) with radial basis function (RBF) kernel is an effective nonlinear method for the quantitative calibration in the visible–near-infrared (Vis–NIR) spectral region. However, the nonlinear effect and high-dimensional spectrum data influence the prediction accuracy and complexity of modeling procedures. This article presents a fuzzy optimization strategy to improve the performance of the RBF LSSVR model in Vis–NIR quantitative determination of pomelo maturity. In the proposed strategy, a linguistic iterative mode is introduced for optimizing RBF kernel parameters. The input variables of the model are the informative features extracted through fuzzy transform principal component analysis algorithm, and the output was a polynomial equation of the inputs. In this article, pomelo maturity is recorded using the quantitative indices of L *, a *, and b *. The Vis–NIR spectral data of Pomelo samples are first converted to a set of fuzzy-transformed principal components and inputted into a fuzzy-optimized LSSVR model for calibration, validation, and test. Parameter uncertainty is evaluated to verify the effectiveness of the proposed strategy. Experimental results show that the proposed fuzzy optimization strategy is feasible for reducing the computational complexity of the BRF LSSVR model, and the predictions on L *, a *, and b * are much appreciable. The proposed fuzzy optimization strategy based on the linguistic iteration mode is considered as the effective implementation for calibration models in the spectroscopy technology for rapid prediction of fruit maturity.

A Fuzzy Optimization Strategy for the Implementation of RBF LSSVR Model in Vis–NIR Analysis of Pomelo Maturity

Over the last two decades, application of Data envelopment analysis (DEA) in transportation problems have gained considerable research attention. This paper presents a literature review and classification of the applications of DEA in transportation systems (TSs). First by classifying 40 papers from 2007 to 2018, the origins of DEA in transportation problems have been reviewed. Then the development and an overall view of DEA applications in TSs have been presented. We have classified the applications of DEA into six different contexts. In each context, published papers have deeply been analyzed. Content of analysis includes “Number of published papers during the time”, “target journals”, “countries”, “keyword frequency”, “most cited papers”, “map of most co-cited publications”. More important, we reported the “inputs and outputs variables” used in each paper. Further “a review of the selected papers” and “gaps/future research directions” have been given within each cluster. The results show that DEA is one of the most useful approach in evaluating TSs for policy makers. On the other hand, DEA can help the decision makers in transportation especially regarding environmental factors, sustainable development and eco-design. Finally, we proposed subjects for future researches including guidance for new studies in the field of DEA applications in TSs.

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The origins, development and future directions of data envelopment analysis approach in transportation systems

Big GIS analytics framework for agriculture supply chains: A literature review identifying the current trends and future perspectives

Aims & Scope Peer-to-Peer Networking and Applications (P2PNA) has received significant attention from both academia and industry in recent years. The aim of the Peer-to-Peer Networking and Applications journal is to disseminate state-of-the-art research and development results in this rapidly growing research area, to facilitate the deployment of P2P networking and applications, and to bring together the academic and industry communities, with the goal of fostering interaction to promote further research interests and activities, thus enabling new P2P applications and services. The journal not only will address research topics related to networking and communications theory, but will also consider the standardization, economic, and engineering aspects of P2P technologies, and their impacts on software engineering, computer engineering, networked communication, and security.

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Peer-to-Peer Networking and Applications

This survey paper contains a surprisingly large amount of material and indeed can serve as an introduction to some of ideas and methods of singular perturbation theory. In continuation of a survey performed earlier, this paper limits its coverage to some standard numerical methods developed by numerous researchers between 2000 and 2005. A summary of the results of some recent methods is presented and this leads to conclusions and recommendations regarding methods to use on singular perturbation problems. Because of space constraints, we considered one-dimensional singularly perturbed boundary value problems only.

A recent survey on computational techniques for solving singularly perturbed boundary value problems

Multi-objective transportation problem (MOTP) is a special case of vector minimization linear optimization problem with equality constraints and the objectives are conflicting in nature. Due to the conflicting nature of objectives, no method is available to find single optimal solution for MOTP. All the methods can find only the compromise solution. This paper presents an efficient method for solving MOTP to find fuzzy efficient and compromise solution using the qualities of three well known approaches i.e. (i) fuzzy programming, (ii) goal programming, (iii) interactive programming. In this approach, fuzzy goals are decided by the decision maker (DM) for each objectives and membership functions are constructed for each objective. Then the method is developed using fuzzy set theory and the best quality of the developed method is that the decision maker is focussed only in the part of evaluation of the solution at each step using the acceptable terms and conditions. The present method is the extension of Waeil and Lee (Omega 34:158–166, 2006). To measure the efficiency of the method, some distance metric functions are used and it is verified by two numerical examples. The results are compared with previous reported work for the same numerical problems.

Fuzzy Efficient Interactive Goal Programming Approach for Multi-objective Transportation Problems

This article presents an algorithm for solving fully fuzzy multi-objective linear fractional (FFMOLF) optimization problem. Some computational algorithms have been developed for the solution of fully fuzzy single-objective linear fractional optimization problems. Veeramani and Sumathi (Appl Math Model 40:6148–6164, 2016) pointed out that no algorithm is available for solving a single-objective fully fuzzy optimization problem. Das et al. (RAIRO-Oper Res 51:285–297, 2017) proposed a method for solving single-objective linear fractional programming problem using multi-objective programming. Moreover, it is the fact that no method/algorithm is available for solving a FFMOLF optimization problem. In this article, a fully fuzzy MOLF optimization problem is considered, where all the coefficients and variables are assumed to be the triangular fuzzy numbers (TFNs). So, we are proposing an algorithm for solving FFMOLF optimization problem with the help of the ranking function and the weighted approach. To validate the proposed fuzzy intelligent algorithm, three existing classical numerical problems are converted into FFMOLF optimization problem using approximate TFNs. Then, the proposed algorithm is applied in an asymmetric way. Since there is no algorithm available in the existing literature for solving this difficult problem, we compare the obtained efficient solutions with corresponding existing methods for deterministic problems.

An approach for solving fully fuzzy multi-objective linear fractional optimization problems

Present research deals with more efficient solution of a multi-objective linear fractional (MOLF) optimization problem by using branch and bound method. The MOLF optimization problem is reduced into multi-objective optimization problem by a transformation. The reduced multi-objective optimization problem is converted into single objective optimization problem by giving suitable weight for each objective. The equivalency theorems are established. Weak duality concept is used to compute the bounds for each partition and some theoretical results are also established. The proposed method is motivated by the work of Shen et al. (J Comput Appl Math 223:145–158, 2009). Matlab code is designed for the proposed method to run all the simulated results and it is applied on two numerical problems. The efficiency of the method is measured by comparing with earlier established method.

https://link.springer.com/content/pdf/10.1007%2Fs00521-016-2243-6.pdf

Branch and bound computational method for multi-objective linear fractional optimization problem

This paper presents a new modified technique for order preference by similarity to ideal solution (M-TOPSIS) approach for unraveling stochastic fuzzy multi-level multi-objective fractional decision making problem (ML-MOFDM) problem In the proposed model the coefficients and the scalars of the fractional objectives have a fuzzy nature The right-hand sides are stochastic parameters also, both of the left-hand side coefficients and the tolerance measures are fuzzy kind In this manner, the deterministic-crisp ML-MOFDM model of stochastic fuzzy ML-MOFDM can be gotten utilizing chance constrained strategy with predominance plausibility criteria and the 
$$ \alpha $$

-cut methodology In literature, almost all works on multi-level fractional programming are the crisp version, in which they convert the fractional functions into a linear one using a first order Taylor series which causes rounding off error The proposed M-TOPSIS approach presents a new method for solving such problem without approximating or changing the nature of the problem An algorithm to clear up the M-TOPSIS approach, just as illustrative numerical model is displayed

Pitam Singh

Papers

A recent survey on computational techniques for solving singularly perturbed boundary value problems

Fuzzy Efficient Interactive Goal Programming Approach for Multi-objective Transportation Problems

An approach for solving fully fuzzy multi-objective linear fractional optimization problems

Branch and bound computational method for multi-objective linear fractional optimization problem

A modified TOPSIS approach for solving stochastic fuzzy multi-level multi-objective fractional decision making problem