A NEW VIEWPOINT OF S-CURVE REGRESSION MODEL AND ITS APPLICATION TO CONSTRUCTION MANAGEMENT

2006 ◽  
Vol 15 (02) ◽  
pp. 131-142 ◽  
Author(s):  
TING-YA HSIEH ◽  
MORRIS H. L. WANG ◽  
CHENG-WU CHEN ◽  
CHEN-YUAN CHEN ◽  
SHANG-EN YU ◽  
...  
Keyword(s):  
Regression Model ◽  
Large Scale ◽  
Fuzzy Model ◽  
Least Square Method ◽  
Least Square ◽  
City Government ◽  
Fuzzy Regression ◽  
Small Scale ◽  
Project Control ◽  
S Curve

The least square method is in generally used for curve fitting problems. We here propose a fuzzy S-curve regression model to deal with the case in which the observed data are given by fuzzy numbers. The fuzzy regression curve, obtained for project control and predicting the progress of large-scale or small-scale engineering, is smoothly connected by a Takagi-Sugeno (T-S) fuzzy model. This paper also proposes the concept that the upper bound and lower bound are given instead of the confidence interval when the observed data are not obtained exactly. Based on the project cash flow and progress payment records of an example project taken from the Department of Rapid Transit Systems, Taipei City Government, this model is demonstrated and tentative conclusions concerning the model are given. The S-curve equation developed here could be used in a variety of applications related to project control for the management of working capital for construction firms.

Fast Multipole Virtual Boundary Element - Least Square Method for Solving 2-D Elastic Problems

2011 ◽  
Vol 204-210 ◽  
pp. 2196-2201
Author(s):  
Yan Tao Jiang ◽  
Si Tian Chen ◽  
Cheng Hua Li
Keyword(s):  
Boundary Element ◽  
Large Scale ◽  
Fast Multipole Method ◽  
Main Idea ◽  
Least Square Method ◽  
Least Square ◽  
Fast Multipole ◽  
Large Scale Problems ◽  
Virtual Boundary ◽  
Virtual Boundary Element

In this paper, the fast multipole virtual boundary element - least square method (Fast Multipole VBE - LSM) is proposed and used to simulate 2-D elastic problems, which is based on the fast multipole method (FMM) and virtual boundary element - least square method (VBE - LSM).The main idea of the method is to change computational model by applying the FMM to conventional VBE - LSM. The memory and operations could be reduced to be of linear proportion to the degree of freedom (DOF) and large scale problems could be effectively solved on a common desktop with this method. Numerical results show that this method holds virtues of high feasibility, accuracy and efficiency. Moreover, the idea of this method can be generalized and extended in application.

Studying Fitting Effect by ANFIS in the Electrodialysis Process

2011 ◽  
Vol 268-270 ◽  
pp. 336-339
Author(s):  
Guo Lin Jing ◽  
Wen Ting Du ◽  
Quan Zhou ◽  
Song Tao Li
Keyword(s):  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Back Propagation ◽  
Fuzzy Model ◽  
Least Square Method ◽  
Least Square ◽  
Back Propagation Algorithm ◽  
Inference System ◽  
Error Back Propagation ◽  
Error Back Propagation Algorithm

Fuzzy system is known to predict model in the electrodialysis process. This paper aimed to study fitting effect by ANFIS in a laboratory scale ED cell. Separation percent of NaCl solution is mainly as a function of concentration, temperature, flow rate and voltage. Besides, ANFIS(Adaptive Neuro-Fuzzy Inference System) based on Sugeno fuzzy model, its structure was similar to neural network and could generate fuzzy rules automatically, using the error back propagation algorithm and least square method to adjust the parameters of fuzzy inference system. We obtained fitted values of separation percent by ANFIS. Separation percent from experiments compared with the fitted values of separation percent. The result is shown that the correlation coefficient is 0.988. Therefore, it is verified as a good performance in the electrodialysis process.

scholarly journals Community-based landslide hazard probability and risk assessment: A case in west Hubei, China

2019 ◽  
Author(s):  
Sheng Fu ◽  
Lixia Chen ◽  
Tsehaie Woldai ◽  
Kunlong Yin ◽  
Lei Gui ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Return Period ◽  
Probabilistic Method ◽  
Least Square Method ◽  
Landslide Hazard ◽  
Least Square ◽  
Small Scale ◽  
Power Law Distribution ◽  
Inverse Gamma ◽  
Landslide Volume

Abstract. Small communities living in high mountainous terrains, in Hubei Province are often impacted by landslide hazard. Past work by China Geology Survey focused only on hazard assessment at 1 : 100 000 scales. In this study, we conducted a more-detailed semiquantitative landslide and risk assessment at a community level and scale of 1 : 10 000. We applied the probabilistic method to assess the landslide spatial, temporal and size probabilities while the landslide hazard and risk assessment were considered for four return periods (5, 10, 20 and 50 years) and two size scenarios (landslide volume). The spatial probability by susceptibility mapping with an accuracy of 84 % indicates that Quaternary deposits and weathered eluvium from Ordovician limestone are the two major controlling factors. Most building areas in hazard maps are located at the foot of major slopes where hazard probabilities are very high. We computed the loss of lives and properties for each slope. The result shows that 1530 people and 126 million RMB economics were at risk of being affected by landslides with a 50-year return period and a landslide volume of fifty thousand cubic meters. Meanwhile, the longer the return period, the higher the hazard probability is. Compared with the function by ordinary least square method, classic inverse gamma and power law distribution of landslide magnitude and frequency are not suitable for landslide size probability analysis in the study area. The proposed procedure is proved to be more useful to complement risk assessment on the small scale of 100 000 in west Hubei, China.

Experimental Study on Coupling Characteristics of Cutting Heat and Cutting Vibration Under Different Tool Wear States

2021 ◽  
Author(s):  
Songyuan Li ◽  
Shuncai Li ◽  
Yuting Hu ◽  
Eugene Popov
Keyword(s):  
Regression Model ◽  
Temperature Rise ◽  
Mechanical Vibration ◽  
Cutting Temperature ◽  
Least Square Method ◽  
Cutting Parameters ◽  
Least Square ◽  
Cutting Heat ◽  
Cutting Vibration ◽  
Coupling Characteristics

Abstract The thermo-mechanical-vibration coupling characteristics of turning system has always been an important research topic in the field of machining, and the material, states and performance of cutting tools will directly affect this coupling characteristics. In this paper, a synchronous testing system for cutting temperature and cutting vibration is built to collect the cutting temperature and cutting vibration near the tip of three worn tools D1 (new blade), D2 (moderately worn blade) and D3 (severely worn blade). Based on the test data and the grey correlation theory, the coupling characteristics of cutting temperature rise and cutting vibration of tools in different wear states are analyzed. Based on the experimental data and least square method, (1) the regression model of cutting temperature rise about cutting vibration and cutting parameters (2) the regression model of cutting vibration about cutting temperature rise and cutting parameters have been established respectively. The undetermined parameters and correlation coefficients are obtained by MATLAB software programming. The research show that the coupling of cutting heat and cutting vibration of tools D1 and D2 is one-way coupling, that is, cutting vibration significantly affects cutting heat, but cutting heat has little effect on cutting vibration, while the coupling of cutting heat and cutting vibration of tool D3 is a bidirectional coupling.

scholarly journals Governance and enterprise restructuring: the case of Macedonia

2014 ◽  
Vol 9 (1) ◽  
pp. 147-156 ◽  
Author(s):  
Mico Apostolov
Keyword(s):  
Corporate Governance ◽  
Regression Model ◽  
Financial Institutions ◽  
Large Scale ◽  
Transition Economy ◽  
Small Scale ◽  
Institution Building ◽  
Content Type ◽  
Enterprise Restructuring ◽  
The Republic

Purpose – This paper is a case study of the Republic of Macedonia and focuses on the development of governance and enterprise restructuring. Thus, country's effective corporate governance and corporate control, which impact enterprise restructuring, are essential in the analysis of market-driven restructuring through domestic financial institutions and markets. The data used in this article are analyzed with an econometric regression model, which as employed in this study examines the interrelationships between governance and enterprise restructuring and set of policies that influence the governance patterns. Two basic hypothesis are taken in the analysis: first, governance and enterprise restructuring depend on set of policies, such as, large-scale privatization, small-scale privatization, price liberalization, competition policy, trade and foreign exchange system, banking reform and interest rate liberalization, securities markets and non-bank financial institutions and overall infrastructure reform; and second, governance and enterprise restructuring improves over time due to imposed policies. The paper aims to discuss these issues. Design/methodology/approach – The data used in this article are analyzed with an econometric regression model, which as employed in this study examines the interrelationships between governance and enterprise restructuring and set of policies that influence the governance patterns. Findings – There is still more to be done in order to bring these economies closer to the standards of developed ones. Indeed, it is needed considerable improvement of corporate governance, institution-building to control agency problems and imposing already adopted regulation, as well as, enforcing new enterprise restructuring policies, within existing policies of overall transition economy restructuring. Originality/value – This paper is a contribution to the research developing the business aspects of the Macedonian economy, as there is constant lack of scientific papers that deal with the specific issues of corporate governance and enterprise restructuring.

scholarly journals An adaptive two-stage analog/regression model for probabilistic prediction of small-scale precipitation in France

2018 ◽  
Vol 22 (1) ◽  
pp. 265-286 ◽  
Author(s):  
Jérémy Chardon ◽  
Benoit Hingray ◽  
Anne-Catherine Favre
Keyword(s):  
Regression Model ◽  
Large Scale ◽  
Linear Models ◽  
Transfer Functions ◽  
Small Scale ◽  
Probabilistic Prediction ◽  
Two Stage ◽  
Precipitation Occurrence ◽  
Seasonal Stratification ◽  
Local Weather

Abstract. Statistical downscaling models (SDMs) are often used to produce local weather scenarios from large-scale atmospheric information. SDMs include transfer functions which are based on a statistical link identified from observations between local weather and a set of large-scale predictors. As physical processes driving surface weather vary in time, the most relevant predictors and the regression link are likely to vary in time too. This is well known for precipitation for instance and the link is thus often estimated after some seasonal stratification of the data. In this study, we present a two-stage analog/regression model where the regression link is estimated from atmospheric analogs of the current prediction day. Atmospheric analogs are identified from fields of geopotential heights at 1000 and 500 hPa. For the regression stage, two generalized linear models are further used to model the probability of precipitation occurrence and the distribution of non-zero precipitation amounts, respectively. The two-stage model is evaluated for the probabilistic prediction of small-scale precipitation over France. It noticeably improves the skill of the prediction for both precipitation occurrence and amount. As the analog days vary from one prediction day to another, the atmospheric predictors selected in the regression stage and the value of the corresponding regression coefficients can vary from one prediction day to another. The model allows thus for a day-to-day adaptive and tailored downscaling. It can also reveal specific predictors for peculiar and non-frequent weather configurations.

MANAGING TARGET THE CASH BALANCE IN CONSTRUCTION FIRMS USING A FUZZY REGRESSION APPROACH

2009 ◽  
Vol 17 (05) ◽  
pp. 667-684 ◽  
Author(s):  
CHENG-WU CHEN ◽  
MORRIS H. L. WANG ◽  
JENG-WEN LIN
Keyword(s):  
Fuzzy Model ◽  
Fuzzy Regression ◽  
Capital Management ◽  
Working Capital ◽  
Cash Balance ◽  
Short Term ◽  
Working Capital Management ◽  
Construction Firms ◽  
Financial Strategies ◽  
S Curve

Construction firms that work on a contractual basis are generally more concerned with short-term rather than long-term financial strategies. The main focus in short-term financial strategies is on working capital management (WCM). Cash management is a major factor for achieving good liquidity and profitability. In this study we take into consideration the cash component of working capital management based on the target cash balance. We develop a practical model that should allow Taiwan construction firms to utilize the currently available cash and assets at any point in time in the most rational way. To help understand the issues involved, we first introduce a model developed by Miller and Orr. The relationship between project duration and progress towards completion is most effectively represented in practical construction management by the S-curve. Thus, in this study we plot the fuzzy S-curve regression based on the Takagi-Sugeno (T-S) fuzzy model. The practicality of the model is demonstrated using project cash flow and progress payment records from a sample project. The data are obtained from the Taipei City Government's Department of Rapid Transit Systems. Some tentative conclusions concerning the model are also given.

scholarly journals Region-wide comprehensive implementation of roguing infected trees, tree replacement, and insecticide applications successfully controls citrus HLB

2020 ◽  
Author(s):  
Xiaoyong Yuan ◽  
Cixiang Chen ◽  
Renato Bassanezi ◽  
Feng Wu ◽  
Zheng Feng ◽  
...  
Keyword(s):  
Regression Model ◽  
Large Scale ◽  
Regional Level ◽  
Economic Feasibility ◽  
Small Scale ◽  
Comprehensive Strategy ◽  
Endemic Diseases ◽  
Dynamic Regression Model ◽  
Partial Implementation ◽  
Citrus Disease

Huanglongbing (HLB) is a devastating citrus disease worldwide. A three-pronged approach to controlling HLB has been suggested, namely, removal of HLB-symptomatic trees, psyllid control, and replacement with HLB-free trees. However, such a strategy did not lead to successful HLB control in many citrus producing regions. We hypothesize this is because of the small-scale or incomprehensive implementation of the program, conversely, a comprehensive implementation of such a strategy at regional level can successfully control HLB. Here we investigated the effects of region-wide comprehensive implementation of this scheme to control HLB in Gannan region, China, with a total planted citrus acreage of over 110,000 ha from 2013–2019. With the region-wide implementation of comprehensive HLB management, overall HLB incidence in Gannan decreased from 19.71% in 2014 to 3.86% in 2019. A partial implementation of such a program (without a comprehensive inoculum removal) at the regional level in Brazil resulted in HLB incidence increasing from 1.89% in 2010 to 19.02% in 2019. A dynamic regression model analyses predicated that in a region-wide comprehensive implementation of such a program, HLB incidence would be controlled to a level of less than 1%. Economic feasibility analyses showed that average net profits were positive for groves that implemented the comprehensive strategy, but negative for groves without such a program over a ten-year period. Overall, the key for the three-pronged program to successfully control HLB control is the large scale (region-wide) and comprehensiveness in implementation. This study provides valuable information to control HLB and other endemic diseases worldwide.

scholarly journals Efektivitas Program Pembangunan PSP terhadap Etos Kerja Petani Desa Ngadisuko, Kabupaten Trenggalek, Jawa Timur

2021 ◽  
Vol 17 (2) ◽  
pp. 177-193
Author(s):  
Iklil Siffana ◽  
Ugik Romadi ◽  
Gunawan Gunawan
Keyword(s):  
Regression Model ◽  
Model Test ◽  
Least Square Method ◽  
Likert Scale ◽  
Significant Degree ◽  
Least Square ◽  
Primary Method ◽  
Ordinary Least Square

This research focused on the influence of PSP Development Program’s (Farming Infrasturcture) toward farmer’s working ethos in Ngadisuko village from February to July 2020. This research was focused to examinethe effectiveness of the Farming Machineries Program’s and Subdisized Fertilizer Program’s toward farmer’s working ethos. Primary method used in this research are closed quetionaire survey with Likert scale using sample of 90 farmers tested dan regression model test based on Ordinary Least Square method. The result showed that there is significant degree of influence; simultaneously between farming machineries and subsidized fertilizer and effectivity toward farmer’s working ethos. However partially inter-variable test showed there is no significant degree of influence toward working ethos and has low influence for 22,5%. This is due to many problems in the implementation of programs aren’t perfect and must be immediately fixed.

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