Forecasting breakup water levels at Fort McMurray, Alberta, using multiple linear regression

2006 ◽  
Vol 33 (9) ◽  
pp. 1227-1238 ◽  
Author(s):  
C Mahabir ◽  
F E Hicks ◽  
C Robichaud ◽  
A Robinson Fayek
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Meteorological Data ◽  
Linear Regression Analysis ◽  
Statistical Modelling ◽  
Water Levels ◽  
River Ice ◽  
Fort Mcmurray ◽  
Ice Jam ◽  
Ice Breakup

Spring breakup on northern rivers can result in ice jams that present severe flood risk to adjacent communities. Such events can occur extremely rapidly, leaving little or no advanced warning to residents. Fort McMurray, Alberta, is one such community, and at present no forecasting model exists for this site. Many of the previous studies regarding ice jam flood forecasting methods, in general, cite the lack of a comprehensive database as an obstacle to statistical modelling. This paper documents the development of an extensive database containing 106 variables, and covering the period from 1972 to 2004, that was created for ice jam forecasting on the Athabasca River. Through multiple linear regression analysis, equations were developed to model the maximum water level during spring breakup. The optimal model contained a combination of hydrological and meteorological data collected from early fall until the day before river ice breakup. The number of historical years of data, rather than the scope of variables, was found to be the major limitation in verifying the results presented in this study.Key words: river ice, breakup jam, multiple linear regression.

Ice jam mitigation

1990 ◽  
Vol 17 (5) ◽  
pp. 675-685 ◽  
Author(s):  
Harold S. Belore ◽  
Brian C. Burrell ◽  
Spyros Beltaos
Keyword(s):  
Key Words ◽  
Carrying Capacity ◽  
Flood Control ◽  
Human Life ◽  
Water Levels ◽  
Economic Losses ◽  
River Ice ◽  
Ice Jams ◽  
Ice Jam ◽  
Ice Breakup

In Canada, flooding due to the rise in water levels upstream of an ice jam, or the temporary exceedance of the flow and ice-carrying capacity of a channel upon release of an ice jam, has resulted in the loss of human life and extensive economic losses. Ice jam mitigation is a component of river ice management which includes all activities carried out to prevent or remove ice jams, or to reduce the damages that may result from an ice jam event. This paper presents a brief overview of measures to mitigate the damaging effects of ice jams and contains a discussion on their application to Canadian rivers. Key words: controlled ice breakup, flood control, ice jams, ice management, river ice.

scholarly journals Cluster and regression analysis for predicting salinity in groundwater

2018 ◽  
Vol 192 ◽  
pp. 02007
Author(s):  
Phiraphat Aphiphan ◽  
Uma Seeboonruang ◽  
Somyot Kaitwanidvilai
Keyword(s):  
Electrical Conductivity ◽  
Regression Analysis ◽  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Water Levels ◽  
Groundwater Salinity ◽  
Groundwater Levels

Groundwater salinity is a major problem particularly in the northeastern region of Thailand. Saline groundwater can cause widespread saline soil problem resulting in reducing agricultural productivity as in the Lower Nam Kam River Basin. In order to better manage the salinity problem, it is important to be able to predict the groundwater salinity. The objective of this research was to create a cluster-regression model for predicting the groundwater salinity. The indicator of groundwater salinity in this study was electrical conductivity because it was simple to measure in field. Ninety-eight parameters were measured including precipitation, surface water levels, groundwater levels and electrical conductivity. In this study, the highest groundwater salinity at 3 wells was predicted using the combined cluster and multiple linear regression analysis. Cross correlation and cluster analysis were applied in order to reduce the number of parameters to effectively predict the quality. After the parameter selection, multiple linear regression was applied and the modeling results obtained were R2 of 0.888, 0.918, and 0.692, respectively. This linear regression model technique can be applied elsewhere in the similar situation.

PENGARUH FAKTOR-FAKTOR INTERNAL PERBANKAN TERHADAP NON PERFORMING FINANCING PADA BANK UMUM SYARIAH

2019 ◽  
Vol 6 (2) ◽  
pp. 115-130
Author(s):  
Eka Ambara Harci Putranta ◽  
Lilik Ambarwati
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Capital Adequacy ◽  
Annual Reports ◽  
Regression Methods ◽  
Capital Adequacy Ratio ◽  
Negative Effect ◽  
Independent Variable

The study aims to analyze the influence of internal banking factors in the form of: Capital Adequency Ratio (CAR), Financing to Deposit Ratio (FDR) and Total Assets (TA) to Non Performing Financing at Sharia Banks. This research method used multiple linear regression analysis with the help of SPSS 16.00 software which is used to see the influence between the independent variables in the form of Capital Adequacy Ratio (CAR), Financing to Deposit Ratio (FDR) and Total Assets (TA) to Non Performing Financing. The sample of this study was 3 Islamic Commercial Banks, so there were 36 annual reports obtained through purposive sampling, then analyzed using multiple linear regression methods. The results showed that based on the F Test, the independent variable had an effect on the NPF, indicated by the F value of 17,016 and significance of 0,000, overall the independent variable was able to explain the effect of 69.60%. While based on the partial t test, showed that CAR has a significant negative effect, Total assets have a significant positive effect with a significance value below 0.05 (5%). Meanwhile FDR does not affect NPF.

ANALISIS PENGARUH INFLASI, KURS DAN IHSG TERHADAP RETURN REKSA DANA SAHAM PT NIKKO SECURITIES INDONESIA PERIODE 2014-2017

2019 ◽  
Vol 2 (2) ◽  
pp. 103
Author(s):  
Muhammad Rois Rois ◽  
Manarotul Fatati Fatati ◽  
Winda Ihda Magfiroh
Keyword(s):  
Regression Analysis ◽  
Exchange Rate ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Stock Price ◽  
Price Index ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Equity Fund ◽  
Stock Price Index

This study aims to determine the effect of Inflation, Exchange Rate and Composite Stock Price Index (IHSG) to Return of PT Nikko Securities Indonesia Stock Fund period 2014-2017. The study used secondary data obtained through documentation in the form of PT Nikko Securities Indonesia Monthly Net Asset (NAB) report. Data analysis is used with quantitative analysis, multiple linear regression analysis using eviews 9. Population and sample in this research are PT Nikko Securities Indonesia. The result of multiple linear regression analysis was the coefficient of determination (R2) showed the result of 0.123819 or 12%. This means that the Inflation, Exchange Rate and Composite Stock Price Index (IHSG) variables can influence the return of PT Nikko Securities Indonesia's equity fund of 12% and 88% is influenced by other variables. Based on the result of the research, the variables of inflation and exchange rate have a negative and significant effect toward the return of PT Nikko Securities Indonesia's equity fund. While the variable of Composite Stock Price Index (IHSG) has a negative but not significant effect toward Return of Equity Fund of PT Nikko Securities Indonesia

An Empirical Study of Investor Attitudinal Factors Influencing Herd Behavior: Evidence from Pakistan Stock Exchange

2019 ◽  
Vol 12 (1) ◽  
pp. 1-11
Author(s):  
Faid Gul ◽  
Karamat Khan
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Psychological Factors ◽  
Stock Exchange ◽  
Linear Regression Analysis ◽  
Primary Data ◽  
Herd Behavior ◽  
Individual Investor ◽  
Decision Accuracy ◽  
Attitudinal Factors

Behavioral Finance is an evolving field that studies how psychological factors affect decision making under uncertainty. Herding behavior is one of the psychological factors that instigate investor to mimic the actions of other investors in the market rather than using his personal assessments. This study seeks to find the influence of certain attitudinal factors namely, decision conformity, hasty decision, mood, decision accuracy, and overconfidence, on the individual investor tendency to embrace herd behavior. Primary data for the study are collected using structured questionnaires from a sample of 194 investors who are trading at Islamabad and Lahore branches of Pakistan Stock Exchange. Multiple linear regression analysis is used to test the hypotheses of this study. Findings of this study provide evidence that attitudinal factors have a significant influence on investor’s tendency to take on herd behavior. It is concluded from the results of multiple linear regression that decision conformity, mood, and decision accuracy have a significant impact on individual investor tendency to adopt herd behavior. However, investor hasty decision and overconfidence is insignificant predictors of herd behavior. Keywords: Decision conformity, Hasty decision, Mood, Decision accuracy, Overconfidence, Herd behavior

PENGARUH LOKASI, KUALITAS PRODUK TABUNGAN, KUALITAS PELAYANAN TERHADAP KEPUASAN NASABAH DALAM MENABUNG DI BMT ADZKIYAH KHIDMATUL UMMAH DI KOTA METRO

2019 ◽  
Vol 3 (2) ◽  
pp. 439
Author(s):  
Suwarto Suwarto ◽  
Risa Anggraini
Keyword(s):  
Linear Regression ◽  
Customer Satisfaction ◽  
Service Quality ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Requirements Analysis ◽  
Primary Data ◽  
Homogeneity Test ◽  
Linearity Test

This research is motivated by customer satisfaction which is a customer action to save. The purpose of this study was to determine the ef ect of location, quality of savings products, service quality on customer satisfaction. In this study using primary data collected by explanatory research methods and sample collection techniques in the form of accidental sampling of BMT customers Adzkiyah Khidmatul Ummah using a questionnaire with a likert skla in BMT Adzkiyah Khidmatul Ummah in Metro City. Testing the instrument requirements used include validity, reliability testing. Requirements analysis using normality test, linearity test, homogeneity test. And analysis tools using multiple linear regression with partial test (t test), simultaneous test (f test), coef icient of determination test (R2). As testing requirements analysis and hypothesis testing. Based on the results of research using multiple linear regression analysis obtained location influences customer satisfaction, the quality of savings products does not af ect customer satisfaction, and service quality influences customer satisfaction.

Predictive Factors for Hamstring Autograft Diameter in Anterior Cruciate Ligament Reconstruction

2019 ◽  
Author(s):  
Willem M.P. Heijboer ◽  
Mathijs A.M. Suijkerbuijk ◽  
Belle L. van Meer ◽  
Eric W.P. Bakker ◽  
Duncan E. Meuffels
Keyword(s):  
Anterior Cruciate Ligament ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Acl Reconstruction ◽  
Cruciate Ligament ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Model ◽  
Gracilis Tendon ◽  
Thigh Circumference ◽  
Anterior Cruciate

AbstractMultiple studies found hamstring tendon (HT) autograft diameter to be a risk factor for anterior cruciate ligament (ACL) reconstruction failure. This study aimed to determine which preoperative measurements are associated with HT autograft diameter in ACL reconstruction by directly comparing patient characteristics and cross-sectional area (CSA) measurement of the semitendinosus and gracilis tendon on magnetic resonance imaging (MRI). Fifty-three patients with a primary ACL reconstruction with a four-stranded HT autograft were included in this study. Preoperatively we recorded length, weight, thigh circumference, gender, age, preinjury Tegner activity score, and CSA of the semitendinosus and gracilis tendon on MRI. Total CSA on MRI, weight, height, gender, and thigh circumference were all significantly correlated with HT autograft diameter (p < 0.05). A multiple linear regression model with CSA measurement of the HTs on MRI, weight, and height showed the most explained variance of HT autograft diameter (adjusted R 2 = 44%). A regression equation was derived for an estimation of the expected intraoperative HT autograft diameter: 1.2508 + 0.0400 × total CSA (mm2) + 0.0100 × weight (kg) + 0.0296 × length (cm). The Bland and Altman analysis indicated a 95% limit of agreement of ± 1.14 mm and an error correlation of r = 0.47. Smaller CSA of the semitendinosus and gracilis tendon on MRI, shorter stature, lower weight, smaller thigh circumference, and female gender are associated with a smaller four-stranded HT autograft diameter in ACL reconstruction. Multiple linear regression analysis indicated that the combination of MRI CSA measurement, weight, and height is the strongest predictor.

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