A multi-scale extended grey target decision method that considers the value distribution information of grey numbers

2017 ◽  
Vol 7 (1) ◽  
pp. 97-110 ◽  
Author(s):  
Wenxin Mao ◽  
Dang Luo ◽  
Huifang Sun
Keyword(s):  
Standard Deviation ◽  
Value Distribution ◽  
Preference Order ◽  
Expected Return ◽  
Content Type ◽  
Multi Scale ◽  
Decision Method ◽  
Multi Attribute Decision Making ◽  
The Mean ◽  
Bull's Eye

Purpose The purpose of this paper is to propose a multi-scale extended grey target decision method for dealing with multi-attribute decision-making problems with interval grey numbers whose value distribution information is asymmetrical. Design/methodology/approach First, the whitenization weight function (WWF) was adopted to show the value distribution information of interval grey numbers. The definitions of kernel, degree of greyness, relative kernel and whitenization standard deviation of interval grey numbers were given based on the WWF. Then, the relative kernel grey target and whitenization standard deviation grey target were constructed to take full advantage of the owned decision information. Finally, the relative bull’s-eye coefficient was proposed to rank the preference order of all alternatives. Findings The relative bull’s-eye coefficient reflects the influence of the decision information on decision results with respect to the mean level and value distribution of attribute values. Thus, the decision-maker could set the return and risk adjustment coefficient according to their preferences and select the optimal alternative with a high expected return and low risk. Originality/value The paper considers the valve distribution information of interval grey numbers, and a novel definition for kernels, degrees of greyness, relative kernels and whitenization standard deviations, which are given based on the WWF. The paper not only considers the influence of mean levels of decision information over decision results, but also takes the value distribution information into account.

Multi-attribute grey target decision method with three-parameter interval grey number

2016 ◽  
Vol 6 (2) ◽  
pp. 270-280 ◽  
Author(s):  
Ye Li ◽  
Shanli Zhu ◽  
San-dang Guo
Keyword(s):  
Decision Making ◽  
Distance Measure ◽  
Ranking Method ◽  
Content Type ◽  
Uncertain Environment ◽  
Decision Method ◽  
Multi Attribute Decision Making ◽  
Parameter Interval ◽  
Grey Number ◽  
Bull's Eye

Purpose – The purpose of this paper is to propose the grey target decision method based on three-parameter interval grey number for dealing with multi-attribute decision-making problems under uncertain environment. Design/methodology/approach – First, the kernel and ranking method of three-parameter interval grey number are defined, which is the basis of determining the positive and negative bull’s-eye. Next, a new distance measure of three-parameter interval grey number is defined in view of the importance of the “center of gravity” point. Furthermore, a new comprehensive bull’s-eye distance is proposed based on the kernel which integrates the distance between different attributes to the positive and negative bull’s-eye. Then attribute weights are obtained by comprehensive bull’s-eye distance minimum and grey entropy maximization. Findings – The paper provides a grey target decision method based on three-parameter interval grey number and example analysis shows that the method proposed in this paper is more reasonable and effective. Research limitations/implications – If we have a better understanding of the distribution characteristics of three-parameter interval grey number, it is possible to have a more reasonable measure of the distance of three-parameter interval grey number. Practical implications – The paper provides a grey target decision method, which can help decision maker deal with multi-attribute decision-making problems under uncertain environment. Originality/value – This paper proposed the kernel and ranking method of three-parameter interval grey number, and defined a new distance measure of three-parameter interval grey number and proposed a new comprehensive bull’s-eye distance, Furthermore, this paper structured a grey target decision method based on three-parameter interval grey number.

Rigorous time-domain analysis of statistically oriented graphene sheet fluctuations

2017 ◽  
Vol 36 (5) ◽  
pp. 1351-1363 ◽  
Author(s):  
Athanasios N. Papadimopoulos ◽  
Stamatios A. Amanatiadis ◽  
Nikolaos V. Kantartzis ◽  
Theodoros T. Zygiridis ◽  
Theodoros D. Tsiboukis
Keyword(s):  
Monte Carlo ◽  
Standard Deviation ◽  
Finite Difference ◽  
Surface Waves ◽  
Time Domain ◽  
Finite Difference Time Domain ◽  
Mean Value ◽  
Content Type ◽  
The Mean ◽  
Difference Time

Purpose Important statistical variations are likely to appear in the propagation of surface plasmon polariton waves atop the surface of graphene sheets, degrading the expected performance of real-life THz applications. This paper aims to introduce an efficient numerical algorithm that is able to accurately and rapidly predict the influence of material-based uncertainties for diverse graphene configurations. Design/methodology/approach Initially, the surface conductivity of graphene is described at the far infrared spectrum and the uncertainties of its main parameters, namely, the chemical potential and the relaxation time, on the propagation properties of the surface waves are investigated, unveiling a considerable impact. Furthermore, the demanding two-dimensional material is numerically modeled as a surface boundary through a frequency-dependent finite-difference time-domain scheme, while a robust stochastic realization is accordingly developed. Findings The mean value and standard deviation of the propagating surface waves are extracted through a single-pass simulation in contrast to the laborious Monte Carlo technique, proving the accomplished high efficiency. Moreover, numerical results, including graphene’s surface current density and electric field distribution, indicate the notable precision, stability and convergence of the new graphene-based stochastic time-domain method in terms of the mean value and the order of magnitude of the standard deviation. Originality/value The combined uncertainties of the main parameters in graphene layers are modeled through a high-performance stochastic numerical algorithm, based on the finite-difference time-domain method. The significant accuracy of the numerical results, compared to the cumbersome Monte Carlo analysis, renders the featured technique a flexible computational tool that is able to enhance the design of graphene THz devices due to the uncertainty prediction.

Vision-based target point tracking and aiming method

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiao Bo Liang ◽  
Xinghua Qu ◽  
YuanJun Zhang ◽  
Lianyin Xu ◽  
Fumin Zhang
Keyword(s):  
Standard Deviation ◽  
Target Tracking ◽  
High Precision ◽  
Visual Tracking ◽  
Laser Ranging ◽  
Content Type ◽  
Mean Error ◽  
Wide Range ◽  
The Mean ◽  
Correlation Filtering

Purpose Laser absolute distance measurement has the characteristics of high precision, wide range and non-contact. In laser ranging system, tracking and aiming measurement point is the precondition of automatic measurement. To solve this problem, this paper aims to propose a novel method. Design/methodology/approach For the central point of the hollow angle coupled mirror, this paper proposes a method based on correlation filtering and ellipse fitting. For non-cooperative target points, this paper proposes an extraction method based on correlation filtering and feature matching. Finally, a visual tracking and aiming system was constructed by combining the two-axis turntable, and experiments were carried out. Findings The target tracking algorithm has an accuracy of 91.15% and a speed of 19.5 frames per second. The algorithm can adapt to the change of target scale and short-term occlusion. The mean error and standard deviation of the center point extraction of the hollow Angle coupling mirror are 0.20 and 0.09 mm. The mean error and standard deviation of feature points matching for non-cooperative target were 0.06 mm and 0.16 mm. The visual tracking and aiming system can track a target running at a speed of 0.7 m/s, aiming error mean is 1.74 pixels and standard deviation is 0.67 pixel. Originality/value The results show that this method can achieve fast and high precision target tracking and aiming and has great application value in laser ranging.

Dynamic multi-attribute decision-making method with three-parameter interval grey number based on the prospect theory

2018 ◽  
Vol 8 (4) ◽  
pp. 424-435 ◽  
Author(s):  
Ye Li ◽  
Dongxing Zhang
Keyword(s):  
Decision Making ◽  
Prospect Theory ◽  
Value Function ◽  
Reference Points ◽  
Content Type ◽  
Time Points ◽  
Decision Method ◽  
Multi Attribute Decision Making ◽  
Parameter Interval ◽  
Grey Number

Purpose The purpose of this paper is to propose a dynamic multi-attribute decision-making method based on the prospect theory for dealing with the dynamic multi-attribute decision-making problem with three-parameter interval grey number. Design/methodology/approach First, the kernel and comparison rule of three-parameter interval grey numbers are defined, which are the basis of collecting and sorting grey numbers. Next, the prospect value function is determined in view of the decision-making information with different time points as the reference points. Then, an optimal model for solving the attribute weight and time weight is constructed based on the grey entropy principle. Findings The paper provides a dynamic grey interrelation decision method based on the prospect theory with three-parameter interval grey number, and the example analysis shows that the method proposed in this paper has validity and rationality. Research limitations/implications If we have a better understanding of the weights of different reference points, it is possible to receive a more reasonable expression for the comprehensive prospect utility value function. Practical implications The paper provides a grey interrelation decision method based on the prospect theory, which can help the decision maker deal with the dynamic multi-attribute decision-making problems under the uncertain environment. Originality/value The paper proposes the kernel and ranking method of three-parameter interval grey number, and uses different time points as the reference points to define the prospect value function. Furthermore, this paper structures a dynamic grey interrelation decision method with three-parameter interval grey number based on the prospect theory.

Analyzed relationship between risks and expected returns

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Doan Van Dinh
Keyword(s):  
Standard Deviation ◽  
Portfolio Management ◽  
Management Policy ◽  
Expected Returns ◽  
Expected Return ◽  
Content Type ◽  
Return On Equity ◽  
Financial Investment ◽  
Risk Levels ◽  
The Relationship

PurposeThis study aims to investigate the relationship between risks and the expected return of financial investment because the relationship between them is negative; if the investors agree to the higher level of risk, they have the greater the expected return; therefore, investors always require a degree of proportionality between the risks and returns.Design/methodology/approachThis study applied the standard deviation, variance, coefficient of variation methods and matrix function to measure risks. Besides, the dataset is a return on equity ROE, which is collected in three companies at time series from 2005 to 2020.FindingsWhen the variance or the standard deviation is higher, the return on the securities is higher, but the securities are a higher risk and vice versa. The results showed risk levels of stocks that are 2.509%, 0.367%, 3.666% and the corresponding return mean of 38.68%, 23.99% and 14.02%.Originality/valueThe results support the portfolio management policy appropriately. This study identifies issues for managers, investors and readers to consider: have a comprehensive solution among microcosmic policies, finance policy, investment policy and other policies to control and balance the relationship between risks and returns; have appropriate policies to regulate funds to stimulate investment in the long term.

Statistical analysis of wind resource and energy potential assessment of Quaidabad site, Sindh Pakistan

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zahid Hussain Hulio ◽  
Gm Yousufzai ◽  
Wei Jiang
Keyword(s):  
Standard Deviation ◽  
Wind Speed ◽  
Energy Density ◽  
Wind Shear ◽  
Economic Assessment ◽  
Energy Potential ◽  
Content Type ◽  
Mean Values ◽  
The Mean ◽  
Wind Resource

Purpose Pakistan is an energy starving country that needs continuous supply of energy to keep up its economic speed. The aim of this paper is to assess the wind resource and energy potential of Quaidabad site for minimizing the dependence on fuels and improving the environment. Design/methodology/approach The Quaidabad site wind shear coefficient and turbulence intensity factor are investigated. The two-parameter k and c Weibull distribution function is used to analyze the wind speed of site. The standard deviation of the site is also assessed for a period of a year. The wind power density and energy density are assessed for a period of a year. The economic assessment of energy/kWh is investigated for selection of appropriate wind turbine. Findings The mean wind shear coefficient was observed to be 0.2719, 0.2191 and 0.1698 at 20, 40 and 60 m, respectively, for a period of a year. The mean wind speed is found to be 2.961, 3.563, 3.907 and 4.099 m/s at 20, 40, 60 and 80 m, respectively. The mean values of k parameters were observed to be 1.563, 2.092, 2.434 and 2.576 at 20, 40, 60 and 80 m, respectively, for a period of a year. The mean values of c m/s parameter were found to be 3.341, 4.020, 4.408 and 4.625 m/s at 20, 40, 60 and 80 m, respectively, for a period of a year. The major portion of values of standard deviation was found to be in between 0.1 and 2.00 at 20, 40, 60 and 80 m. The wind power density (W/m2) sum total values were observed to be 351, 597, 792 and 923 W/m2 at 20, 40, 60 and 80 m, respectively, for a period of a year. The mean coefficient of variation was found to be 0.161, 0.130, 0.115 and 0.105 at 20, 40, 60 and 80 m, respectively. The sum total energy density was observed to be 1,157, 2,156, 2,970 and 3,778 kWh/m2 at 20, 40, 60 and 80 m, respectively. The economic assessment is showing that wind turbine E has the minimum cost US$0.049/kWh. Originality/value The Quaidabad site is suitable for installing the utility wind turbines for energy generation at the lowest cost.

scholarly journals Fecal Indole as a Biomarker of Susceptibility to Cryptosporidium Infection

2016 ◽  
Vol 84 (8) ◽  
pp. 2299-2306 ◽  
Author(s):  
Cynthia L. Chappell ◽  
Charles Darkoh ◽  
Lawrence Shimmin ◽  
Naveed Farhana ◽  
Do-Kyun Kim ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Standard Deviation ◽  
Gut Microbiota ◽  
Immune Status ◽  
Infection Intensity ◽  
Cryptosporidium Infection ◽  
Content Type ◽  
Before And After ◽  
Stool Samples ◽  
The Mean

Cryptosporidiumcauses significant diarrhea worldwide, especially among children and immunocompromised individuals, and no effective drug treatment is currently available for those who need it most. In this report, previous volunteer infectivity studies have been extended to examine the association between fecal indole and indole-producing (IP) gut microbiota on the outcome of aCryptosporidiuminfection. Fecal indole concentrations (FICs) of 50 subjects and 19 taxa of common gut microbiota, including six IP taxa (11 subjects) were determined in stool samples collected before and after a challenge withCryptosporidiumoocysts. At the baseline, the mean FIC (± the standard deviation) was 1.66 ± 0.80 mM in those who became infected after a challenge versus 3.20 ± 1.23 mM in those who remained uninfected (P= 0.0001). Only 11.1% of the subjects with a FIC of >2.5 mM became infected after a challenge versus 65.2% of the subjects with a FIC of <2.5 mM. In contrast, the FICs of infected subjects at the baseline or during diarrhea were not correlated with infection intensity or disease severity. The relative abundances (percent) ofEscherichia coli,Bacillusspp., andClostridiumspp. were greater ≥2.5-fold in volunteers with a baseline FIC of >2.5 mM, while those ofBacteroidespyogenes,B. fragilis, andAkkermansiamuciniphilawere greater in those with a baseline FIC of <2.5 mM. These data indicate that some IP bacteria, or perhaps indole alone, can influence the ability ofCryptosporidiumto establish an infection. Thus, preexisting indole levels in the gut join the oocyst dose and immune status as important factors that determine the outcome ofCryptosporidiumexposure.

Site-specific technical and economic analysis of wind power potential and energy generation using Weibull parameters

2018 ◽  
Vol 15 (1) ◽  
pp. 35-53 ◽  
Author(s):  
Zahid Hussain Hulio ◽  
Wei Jiang
Keyword(s):  
Standard Deviation ◽  
Wind Speed ◽  
Economic Analysis ◽  
Wind Power ◽  
Wind Turbines ◽  
Energy Generation ◽  
Site Specific ◽  
Content Type ◽  
Mean Wind Speed ◽  
The Mean

Purpose The purpose of this paper is to find out a new potential site for energy generation to maximize the energy generation via installing utility wind turbines. Design/methodology/approach In this paper, Weibull two-parameter methodologies are used to determine the effectiveness of the wind speed at three different heights including 80, 60 and 30 m. Standard deviation and wind power density (WPD) are also calculated for the site. After analyzing the wind resource, the wind turbine selection is materialized to maximize the energy production, considering the best configuration of the wind turbines that is suitable for the site. In the end, economic aspect is also calculated. Findings The mean Weibull dimensionless parameter k is found to be 2.91, 2.845 and 2.617, respectively. The mean Weibull scale parameter c is found to be 6.736, 6.524 and 6.087 at the heights of 80, 60 and 30 m, respectively. The mean standard deviation is found to be 2.297, 2.249 and 2.157 at the heights of 80, 60 and 30 m at the heights of 80, 60 and 30 m, respectively. Wind power densities are calculated to be 265, 204 and 157.9 W/m2 at the heights of 80, 60 and 30 m, respectively (highest in the month of July when the mean wind speed is 7.707 m/s and WPD is 519 W/m2). Finally, site-specific economic analysis of wind turbines is carried out, which shows $0.0230 per kWh at the height of 80 m. Originality/value The results show that the site is beneficial for the installation of small and large wind turbines.

Wind resource and energy potential assessment of the Sujawal site, Sindh Pakistan

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zahid Hussain Hulio
Keyword(s):  
Standard Deviation ◽  
Wind Speed ◽  
Wind Turbine ◽  
Wind Power ◽  
Wind Shear ◽  
Economic Assessment ◽  
Energy Potential ◽  
Content Type ◽  
Mean Values ◽  
The Mean

PurposeThe objective of this paper to assess the wind energy potential of the Sujawal site for minimizing the dependence on fossil fuels.Design/methodology/approachThe site-specific wind shear coefficient and the turbulence model were investigated. The two-parameter, k and c, Weibull distribution function was used to analyze the wind speed of the Sujawal site. The standard deviation of the site was also assessed for a period of a year. Also, the coefficient of variation was carried out to determine the difference at each height. The wind power and energy densities were assessed for a period of a year. The economic assessment of energy/kWh was investigated for selection of appropriate wind turbine.FindingsThe mean wind shear of the Sujawal site was found to be 0.274. The mean wind speed was found to be 7.458, 6.911, 6.438 and 5.347 at 80, 60, 40 and 20 m, respectively, above the ground level (AGL). The mean values of k parameter were observed to be 2.302, 2.767, 3.026 and 3.105 at 20, 40, 60 and 80 m, respectively, for a period of a year. The Weibull c m/s parameter values were found to be 8.415, 7.797, 7.265 and 6.084 m/s at 80, 60, 40 and 20 m, respectively. The mean values of standard deviation were found to be 0.765, 0.737, 0.681 and 0.650 at 20, 40, 60, and 80 m, respectively. The mean wind power density (W/m2) was found to be 287.33, 357.16, 405.16 and 659.58 for 20, 40, 60 and 80 m, respectively. The economic assessment showed that wind turbine 7 had the minimum cost/kWh US$ 0.0298.Originality/valueThe Sujawal site is suitable for installing the utility wind turbines for energy generation at the lowest cost; hence, a sustainable solution.

Information and performance optimization: a study of Indian IPOs during 2005-2012

2017 ◽  
Vol 51 (4) ◽  
pp. 458-471 ◽  
Author(s):  
Sheena Chhabra ◽  
Ravi Kiran ◽  
A.N. Sah ◽  
Vikas Sharma
Keyword(s):  
Initial Public Offerings ◽  
Performance Optimization ◽  
Investment Decision ◽  
Mixed Integer ◽  
Expected Return ◽  
Content Type ◽  
Public Offerings ◽  
The Mean ◽  
And Performance ◽  
Global Investors

Purpose The purpose of this paper is to focus on examining the first day returns of initial public offerings (IPOs) and the role of information on their performance. The study tries to optimize the returns of the new issues during 2005-2012 with risk as a constraint. Design/methodology/approach The initial returns are measured through the market-adjusted excess return and the risk associated with the new issue is measured through underwriters’ reputation. The returns have been optimized through a mixed integer linear problem using the Maple software. Findings The previous studies show that various informational variables affect the listing day returns significantly. The results of the present study indicate that the mean of initial returns for IPOs during 2005-2012 is 18.03 and the mean risk for these issues is 0.46. The findings also suggest that the optimal returns are obtained in the pre-recession era (2005-2008) and the value for the same is 50.02 percent. Originality/value The current study contributes in the investment decisions for global investors as every investor wants to maximize his/her returns. The optimal returns with risk as a constraint will help the investors in improving their investment decision as a prudent investor does not aim solely at maximizing the expected return of an investment but is also interested in optimizing with the minimization of risk.

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