Interval Distribution Power Flow with Relative-Distance-Measure Arithmetic

2021 ◽  
pp. 1-1
Author(s):  
Viet Cuong Ngo ◽  
Wenchuan Wu ◽  
Bing Wang ◽  
Yanling Du ◽  
Tuan Nguyen Ngoc
Keyword(s):  
Power Flow ◽  
Distance Measure ◽  
Relative Distance ◽  
Interval Distribution

The framework of data-driven and multi-criteria decision-making for detecting unbalanced bidding

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Huimin Li ◽  
Limin Su ◽  
Jian Zuo ◽  
Xiaowei An ◽  
Guanghua Dong ◽  
...  
Keyword(s):  
Decision Making ◽  
Distance Measure ◽  
Public Procurement ◽  
Unit Price ◽  
Data Driven ◽  
Relative Distance ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Content Type ◽  
The Government

PurposeUnbalanced bidding can seriously imposed the government from obtaining the best value for the taxpayers' money in public procurement since it increases the owner's cost and decreases the fairness of the competitive bidding process. How to detect an unbalanced bid is a challenging task faced by theoretical researchers and practical actors. This study aims to develop an identification method of unbalanced bidding in the construction industry.Design/methodology/approachThe identification of unbalanced bidding is considered as a multi-criteria decision-making (MCDM) problem. A data-driven unit price database from the historical bidding document is built to present the reference unit prices as benchmarks. According to the proposed extended TOPSIS method, the data-driven unit price is chosen as the positive ideal solution, and the unit price that has the furthest absolute distance measure as the negative ideal solution. The concept of relative distance is introduced to measure the distances between positive and negative ideal solutions and each bidding unit price. The unbalanced bidding degree is ranked by means of relative distance.FindingsThe proposed model can be used for the quantitative evaluation of unbalanced bidding from a decision-making perspective. The identification process is developed according to the decision-making process. The finding shows that the model will support owners to efficiently and effectively identify unbalanced bidding in the bid evaluation stage.Originality/valueThe data-driven reference unit prices improve the accuracy of the benchmark to evaluate the unbalanced bidding. The extended TOPSIS model is applied to identify unbalanced bidding; the owners can undertake objective decision-making to identify and prevent unbalanced bidding at the stage of procurement.

Relative Distance Measure Model for the Fuzzy Synthetic Evaluation of Subgrade Stability in Seasonal Frozen Area

2012 ◽  
Vol 178-181 ◽  
pp. 1213-1217
Author(s):  
Han Bing Liu ◽  
Yi Ming Xiang ◽  
Hui Wang ◽  
Yan Yi Sun
Keyword(s):  
Structural Reliability ◽  
Distance Measure ◽  
Simulation Method ◽  
Relative Distance ◽  
Fuzzy Synthetic Evaluation ◽  
Interval Numbers ◽  
Evaluation Indexes ◽  
Measure Model ◽  
Grading Standards ◽  
Synthetic Evaluation

Based on the fuzziness and uncertainty of the subgrade stability in seasonal frozen area, the relative distance measure model with evaluation indexes and weights in the form of interval numbers is presented for the fuzzy synthetic evaluation of the subgrade stability. Firstly, the relative distance measure of each single index between the evaluated subgrade stability and the grading standards is defined. Then, the fuzzy synthetic evaluation model, which considers the functionality and proportionality of evaluation indexes, is established to calculate the comprehensive relative distance measure by using the Monte Carlo simulation method and the sequential relation analysis. Finally, a new decision index of the comprehensive relative distance measure is defined considering the concept of structural reliability, and the stability grade of seasonal frost soil subgrade can be determined by the minimum decision index from the corresponding grading standards. A practical example is given to demonstrate the feasibility and practicability of the proposed model.

A Novel Cooperative Divide-and-Conquer Neural Networks Algorithm

2020 ◽  
pp. 286-317
Author(s):  
Pan Wang ◽  
Yandi Zuo ◽  
Jiasen Wang ◽  
Jian Zhang
Keyword(s):  
Neural Networks ◽  
Distance Measure ◽  
Classical Method ◽  
Approximation Problem ◽  
Divide And Conquer ◽  
Relative Distance ◽  
Data Sets ◽  
Main Task ◽  
Data Set ◽  
Testing Error

Dynamic modularity is one of the fundamental characteristics of the human brain. Cooperative divide and conquer strategy is a basic problem solving approach. This chapter proposes a new subnet training method for modular neural networks with the inspiration of the principle of “an expert with other capabilities.” The key point of this method is that a subnet learns the neighbor data sets while fulfilling its main task: learning the objective data set. Additionally, a relative distance measure is proposed to replace the absolute distance measure used in the classical method and its advantage is theoretically discussed. Both methodology and empirical study are presented. Two types of experiments respectively related with the approximation problem and the prediction problem in nonlinear dynamic systems are designed to verify the effectiveness of the proposed method. Compared with the classical learning method, the average testing error is dramatically decreased and more stable. The superiority of the relative distance measure is also corroborated. Finally, a mind-gut frame is proposed.

scholarly journals Computing with words with the use of inverse RDM models of membership functions

2015 ◽  
Vol 25 (3) ◽  
pp. 675-688 ◽  
Author(s):  
Andrzej Piegat ◽  
Marcin Pluciński
Keyword(s):  
Interval Arithmetic ◽  
Distance Measure ◽  
Specific Problem ◽  
Human Mind ◽  
Relative Distance ◽  
Fuzzy Membership ◽  
Computing With Words ◽  
Membership Functions ◽  
Fuzzy Membership Functions ◽  
Flight Delay

Abstract Computing with words is a way to artificial, human-like thinking. The paper shows some new possibilities of solving difficult problems of computing with words which are offered by relative-distance-measure RDM models of fuzzy membership functions. Such models are based on RDM interval arithmetic. The way of calculation with words was shown using a specific problem of flight delay formulated by Lotfi Zadeh. The problem seems easy at first sight, but according to the authors’ knowledge it has not been solved yet. Results produced with the achieved solution were tested. The investigations also showed that computing with words sometimes offers possibilities of achieving better problem solutions than with the human mind.

Methodological Research for Modular Neural Networks Based on “an Expert With Other Capabilities”

2018 ◽  
Vol 26 (2) ◽  
pp. 104-126
Author(s):  
Pan Wang ◽  
Jiasen Wang ◽  
Jian Zhang
Keyword(s):  
Neural Networks ◽  
Distance Measure ◽  
Approximation Problem ◽  
Relative Distance ◽  
Data Sets ◽  
Main Task ◽  
Learning Method ◽  
Data Set ◽  
Modular Neural Networks ◽  
Testing Error

This article contains a new subnet training method for modular neural networks, proposed with the inspiration of the principle of “an expert with other capabilities”. The key point of this method is that a subnet learns the neighbor data sets while fulfilling its main task: learning the objective data set. Additionally, a relative distance measure is proposed to replace the absolute distance measure used in the classical subnet learning method and its advantage in the general case is theoretically discussed. Both methodology and empirical study of this new method are presented. Two types of experiments respectively related with the approximation problem and the prediction problem in nonlinear dynamic systems are designed to verify the effectiveness of the proposed method. Compared with the classical subnet learning method, the average testing error of the proposed method is dramatically decreased and more stable. The superiority of the relative distance measure is also corroborated.

Center of Mass Theorem and the Separation of Variables for Two-Body System on a Three-Dimensional Sphere

2020 ◽  
Vol 23 (3) ◽  
pp. 306-311
Author(s):  
Yu. Kurochkin ◽  
Dz. Shoukavy ◽  
I. Boyarina
Keyword(s):  
Constant Curvature ◽  
Jacobi Equation ◽  
Separation Of Variables ◽  
Center Of Mass ◽  
Three Dimensional ◽  
Relative Distance ◽  
Dimensional Sphere ◽  
Body System ◽  
Spaces Of Constant Curvature ◽  
Hamilton Jacobi Equation

The immobility of the center of mass in spaces of constant curvature is postulated based on its definition obtained in [1]. The system of two particles which interact through a potential depending only on the distance between particles on a three-dimensional sphere is considered. The Hamilton-Jacobi equation is formulated and its solutions and trajectory equations are found. It was established that the reduced mass of the system depends on the relative distance.

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