Effects of Neighborhood Inequality on the Relative Distance between Objective Position and Subjective Identification

2017 ◽  
Vol 27 (1) ◽  
pp. 85-106
Author(s):  
Andrew Ho Kim ◽  
Muncho Kim ◽  
Seoungho Ryu
Keyword(s):  
Relative Distance ◽  
Neighborhood Inequality

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.

Relative Distance-Aware Data Delivery Scheme for Delay Tolerant Mobile Sensor Networks

2010 ◽  
Vol 21 (3) ◽  
pp. 490-504 ◽  
Author(s):  
Fu-Long XU ◽  
Ming LIU ◽  
Hai-Gang GONG ◽  
Gui-Hai CHEN ◽  
Jian-Ping LI ◽  
...  
Keyword(s):  
Sensor Networks ◽  
Mobile Sensor Networks ◽  
Relative Distance ◽  
Data Delivery ◽  
Mobile Sensor ◽  
Delay Tolerant

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

scholarly journals NONPARAMETRIC ESTIMATES OF OPTION PRICES AND RELATED QUANTITIES

2019 ◽  
Vol 22 (07) ◽  
pp. 1950040
Author(s):  
GIANLUCA CASSESE
Keyword(s):  
Market Imperfections ◽  
Relative Distance ◽  
Time Behavior ◽  
Option Prices ◽  
Market Returns ◽  
Actual Density ◽  
Nonparametric Estimates ◽  
Absence Of Arbitrage ◽  
Call Function

We propose a new nonparametric technique to estimate the call function based on the superhedging principle. This approach requires minimal assumptions on absence of arbitrage and other market imperfections. The estimates so obtained are then combined with SNP estimates of the actual density of market returns. This permits to investigate the time behavior of the relative distance between the two densities obtained. Our empirical findings suggest that the more the two densities differ, the shorter is time to maturity, suggesting a major role of uncertainty over shorter than longer horizons.

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.

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