scholarly journals A Data-Driven Approach to Trip Generation Modeling for Urban Residents and Non-local Travelers

2020 ◽  
Vol 12 (18) ◽  
pp. 7688
Author(s):  
Fan Yang ◽  
Linchao Li ◽  
Fan Ding ◽  
Huachun Tan ◽  
Bin Ran
Keyword(s):  
Cellular Phone ◽  
Test Methods ◽  
Least Square ◽  
Data Driven ◽  
Urban Residents ◽  
Trip Generation ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Data Driven Approach ◽  
Non Local

Trip generation modeling is essential in transportation planning activities. Previous modeling methods that depend on traditional data collection methods are inefficient and expensive. This paper proposed a novel data-driven trip generation modeling method for urban residents and non-local travelers utilizing location-based social network (LBSN) data and cellular phone data and conducted a case study in Nanjing, China. First, the point of interest (POI) data of the LBSN were classified into various categories by the service type, then, four features of each category including the number of users, number of POIs, number of check-ins, and number of photos were aggregated by traffic analysis zones to be used as explanatory variables for the trip generation models. We used a random tree regression method to select the most important features as the model inputs, and the trip models were established based on the ordinary least square model. Then, an exploratory approach was used to test the performance of each combination of the variables with various test methods to identify the best model for residents’ and travelers’ trip generation functions. The results suggest land use compositions have significant impact on trip generations, and the trip generation patterns are different between urban residents and non-local travelers.

scholarly journals Estimating a global demand model for soybean traffic through the Panama Canal

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Javier Ho ◽  
Paul Bernal
Keyword(s):  
Pacific Northwest ◽  
Least Square ◽  
Panama Canal ◽  
Demand Model ◽  
Department Of Agriculture ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Global Demand ◽  
Alternative Routes ◽  
The U.S

AbstractThis study attempts to fit a global demand model for soybean traffic through the Panama Canal using Ordinary Least Square. Most of the soybean cargo through the interoceanic waterway is loaded on the U.S. Gulf and East Coast ports -mainly destined to East Asia, especially China-, and represented about 34% of total Panama Canal grain traffic between fiscal years 2010–19. To estimate the global demand model for soybean traffic, we are considering explanatory variables such as effective toll rates through the Panama Canal, U.S. Gulf- Asia and U.S. Pacific Northwest- Asia freight rates, Baltic Dry Index, bunker costs, soybean export inspections from the U.S. Gulf and Pacific Northwest, U.S. Gulf soybean basis levels, Brazil’s soybean exports and average U.S. dollar index. As part of the research, we are pursuing the estimation of the toll rate elasticity of vessels transporting soybeans via the Panama Canal. Data come mostly from several U.S. Department of Agriculture sources, Brazil’s Secretariat of Foreign Trade (SECEX) and from Panama Canal transit information. Finally, after estimation of the global demand model for soybean traffic, we will discuss the implications for future soybean traffic through the waterway, evaluating alternative routes and sources for this trade.

scholarly journals The Factors Affecting Land Prices In Housing Location In Sidoarjo Regency

2017 ◽  
Vol 1 (1) ◽  
pp. 37-47
Author(s):  
Partomi Simangunsong ◽  
Arasy Alimudin ◽  
Muh. Barid Nizaruddin Wajdi
Keyword(s):  
Residential Location ◽  
Least Square ◽  
City Center ◽  
Sale Price ◽  
Factors Affecting ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Road Width ◽  
Log Linear ◽  
Road Distance

The need for residential location is one of the basic needs of the community and the attractiveness of the residential location is a unique feature where this feature is not made by the respective occupants, but by external factors from the residential environment in the area. This study aims to analyze the factors that are considered as the basis that affect the price of land. This research uses quantitative approach with associative research method. Linear analysis with quadratic method. Ordinary Least Square (OLS). From the analysis of this research model obtained log-linear F-accounting 70,162 while the value of F-table (0,05; 5,48) is 2,45. because F-count> F-table, Ho means rejected and explanatory variables include Distance to city center, Distance to main road, Distance to toll gate, Road width, and security simultaneously can be explained significantly at land sale price.

scholarly journals Determinants of Household Debt in Malaysia from the year 2010 to 2017

2019 ◽  
Vol 5 (2) ◽  
pp. 91
Author(s):  
Zahariah Mohd Zain ◽  
Nurul Ainun Ahmad Atory Ahmad Atory ◽  
Sarah Amirah Hanafi
Keyword(s):  
Positive Relationship ◽  
Negative Relationship ◽  
Housing Price ◽  
Least Square ◽  
Household Debt ◽  
Macroeconomic Variables ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Independent Variables ◽  
Lending Rate

Household debt has become an issue in the Malaysian economy as it affects the country socially and economically.This study aims to examine the determinants of household debt from the year 2010 until 2017. This study employs the Ordinary Least Square (OLS) method and the macroeconomic variables used in this study are Gross Domestic Product (GDP), base lending rate, unemployment and housing price as independent variables. The results indicate that the trend of household debt in Malaysia has shown a continuous rise from the year 2010 to 2017. GDP, base lending rate and housing price indicate a positive relationship towards household debt while unemployment shows a negative relationship to household debt in Malaysia. All explanatory variables have shown a significant relationship except for GDP. Housing price has been found to be the most significant factor and positively related to household debt. The findings indicate that the higher the price of houses, the higher the household debt will be.

Using Integration of Thermal-Balance Based and Data-Driven Models to Determine Single Duct Variable Air Volume System Cooling Baseline

2013 ◽  
Author(s):  
Gyujin Shim ◽  
Li Song ◽  
Gang Wang
Keyword(s):  
Physical Model ◽  
Least Square Method ◽  
Energy Performance ◽  
Least Square ◽  
Physical Models ◽  
Data Driven ◽  
Lumped Model ◽  
Variable Air Volume ◽  
Data Driven Approach ◽  
Cooling Coil

In order to use real-time energy measurements to identify system operation faults and inefficiencies, a cooling coil energy baseline is studied in an air-handling unit (AHU) through an integration of physical models and a data driven approach in this paper. A physical model for an AHU cooling coil energy consumption is first built to understand equipment mechanism and to determine the variables impacting cooling coil energy performance, and then the physical model is simplified into a lumped model by reducing the number of independent variables needed. Regression coefficients in the lumped model are determined statistically through searching optimal fit using the least square method with short periods of measured data. Experimental results on an operational AHU (8 ton) are presented to validate the effectiveness of this approach with statistical analysis. As a result of this experiment, the proposed cooling energy baselines at the cooling coil have ±20% errors at 99.7% confidence. Six-day data for obtaining baseline is preferred since it shows similar results as 12-day.

scholarly journals Solving Multicollinearity Problem in Linear Regression Model: The Review Suggests New Idea of Partitioning and Extraction of the Explanatory Variables

2021 ◽  
Vol 2 (1) ◽  
pp. 12-20
Author(s):  
Kayode Ayinde, Olusegun O. Alabi ◽  
Ugochinyere Ihuoma Nwosu
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Real Data ◽  
Least Square ◽  
Model Parameters ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Wide Range ◽  
High Level

Multicollinearity has remained a major problem in regression analysis and should be sustainably addressed. Problems associated with multicollinearity are worse when it occurs at high level among regressors. This review revealed that studies on the subject have focused on developing estimators regardless of effect of differences in levels of multicollinearity among regressors. Studies have considered single-estimator and combined-estimator approaches without sustainable solution to multicollinearity problems. The possible influence of partitioning the regressors according to multicollinearity levels and extracting from each group to develop estimators that will estimate the parameters of a linear regression model when multicollinearity occurs is a new econometrics idea and therefore requires attention. The results of new studies should be compared with existing methods namely principal components estimator, partial least squares estimator, ridge regression estimator and the ordinary least square estimators using wide range of criteria by ranking their performances at each level of multicollinearity parameter and sample size. Based on a recent clue in literature, it is possible to develop innovative estimator that will sustainably solve the problem of multicollinearity through partitioning and extraction of explanatory variables approaches and identify situations where the innovative estimator will produce most efficient result of the model parameters. The new estimator should be applied to real data and popularized for use.

scholarly journals The Effect of Foreign Direct Investment on the Unemployment Rate in Saudi Arabia

2020 ◽  
Vol 12 (10) ◽  
pp. 1
Author(s):  
Kolthoom Alkofahi
Keyword(s):  
Saudi Arabia ◽  
Foreign Direct Investment ◽  
Unemployment Rate ◽  
Direct Investment ◽  
Least Square ◽  
Total Output ◽  
Kingdom Of Saudi Arabia ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Job Opportunities

A substantial number of recent studies were devoted to investigating the effects of Foreign direct investment (FDI) on different economic variables. Although the connection between growth and investments is widely acknowledged, the connection between FDI and the unemployment rate is not easy to determine. Taking into consideration the dispute over the true effect of FDI on the host country’s economic performance, the study’s main purpose is to take advantage of the dispute and study the effect of foreign direct investment (FDI) on the unemployment rate (U) in the Kingdom of Saudi Arabia (KSA). Using Ordinary Least Square Model (OLS), the study takes the unemployment rate as a dependent variable, and FDI and Output as two explanatory variables over the period of 2005-2018. The study supports our assumption that the inflows of the FDI and the total output negatively and significantly affect the unemployment rate in the KSA; the inflows of the FDI creates more job opportunities and will reduce the unemployment rate in KSA. Our recommendation is that the KSA government should implement more policies to attract more inflows of “Quality FDI” to attain the maximum goals and to decrease the total unemployment rate.

scholarly journals Electricity Demand in Pakistan: A Household Analysis

2019 ◽  
Vol 1 (2) ◽  
pp. 34-39
Author(s):  
Nauman Ahmed ◽  
Uzma Nisar
Keyword(s):  
Urban Areas ◽  
Positive Impact ◽  
Least Square ◽  
Economic Determinants ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Time Period ◽  
Increasing Demand ◽  
Residential Demand ◽  
Household Analysis

Availability of electricity is essential in modern age because it becomes a necessity of life. The present study used some economic and non-economic determinants that affect household demand for electricity. This study used PSLM survey data for the year 2013-14. The amount of electricity consumed by household was used as dependent variable whereas electricity price, household income, appliances, heating days, region, awareness, and rooms were taken as explanatory variables. Ordinary least square technique (OLS) was used for analysis. The findings of the study showed that Economic and demographic factors are important in determining electricity expenditure. In micro level analysis prices has strong and positive effect on electricity expenditures and it didn’t represent traditional behavior of demand with price. Price and income had positive impact during the period of study with demand for electricity. Expenditure on electricity is fairly higher during summer season. Positive and significant effect is estimated for stock of electricity appliances. Household members have significant effect on electricity expenditure but shows very smaller influence. The dummy variable for region indicates that electricity expenditure is higher for those households who are living in urban areas as compared to rural. Over the time period residential demand of electricity is increasing in Pakistan. As Pakistan is consumption oriented society and demand for appliances is increasing so government should take necessary measures to shift appliances on other resources other than electricity. Increasing use of the appliances increases demand for electricity therefore generation of electricity resources should be increased to meet this increasing demand.

scholarly journals Performance and Obstacles of SMEs: An Empirical Evidence from BRICS Countries

2019 ◽  
Vol 1 (2) ◽  
pp. 113-132
Author(s):  
Madiha Noshad ◽  
Mariam Amjad ◽  
Muhammad Nouman Shafiq ◽  
Seemab Gillani
Keyword(s):  
Positive Impact ◽  
Empirical Evaluation ◽  
Least Square ◽  
Firm Characteristics ◽  
Explanatory Variables ◽  
Ordinary Least Square ◽  
Brics Countries ◽  
Global Factor ◽  
Time Period ◽  
And Performance

This study empirically examines the performance and obstacles of SMEs in BRICS economies. For empirical evaluation, Ordinary Least Square technique has applied by taking the time period between “2000-2017”. Performance has taken as dependent variable and obstacles; firm characteristics and global factor have taken as explanatory variables. Estimated results show that ownership and size have a positive impact on SMEs growth and performance. Age has a negative and significant impact on the performance and growth of SMEs. Technology has a positive and significant impact on the performance of SMEs. Obstacles i.e. courts, crime, access to finance, practices of competitors and electricity has a negative and significant impact on the performance of SMEs. Access to land, infrastructure and workforce has a positive and significant impact on SMEs performance.  It becomes very important for the policymakers or investigators to pay attention towards making SMEs more competent, capable and productive in order to attain the goal of sustainable development and progress.

scholarly journals PENGARUH JUMLAH UANG BEREDAR DAN KURS TERHADAP TINGKAT INFLASI DI INDONESIA SEBELUM DAN SETELAH KRISIS GLOBAL 2009

Media Ekonomi ◽  
2017 ◽  
Vol 18 (3) ◽  
pp. 1
Author(s):  
Hario Aji Hartomo
Keyword(s):  
Exchange Rate ◽  
Money Supply ◽  
Inflation Rate ◽  
Correlation Study ◽  
Test Methods ◽  
Least Square ◽  
Global Crisis ◽  
Ordinary Least Square ◽  
Independent Variables ◽  
Before And After

<p>The objective of this research are to analyzed the effect of Money Supply and Exchange Rate to Inflation Rate in Indonesia before and after Global Crisis at 2008. Type of this research is a correlation study, a research to explain correlation between variables. Dependent Variable used is Inflation Rate (percentages), Independent Variables are Money Supply and Exchange Rate (Indonesian Rupiah to US Dollar). The models will be calculated with OLS (Ordinary Least Square) and Classical Assumption which is excelent in technical, easy to calculate and interpretation. In this case a correlation between dependent variables and independent variables. To determine the inflation rate effect before and after Global Crisis, the other test methods also needed, in example: Normality Test, Autocorrelation Test, Multicolinearity Test, Heteroscedastisity Test and Chow Test. The result from this research determine that Inflation Rate as a dependent variable will significantly influence to Money Supply and Exchange Rate inIndonesia.<br />Keywords : global crisis, inflation rate, money supply</p>

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