Prediction of Municipal Solid Waste Generation in China by Multiple Linear Regression Method

2013 ◽  
Author(s):  
Yuanwei Wei ◽  
Yali Xue ◽  
Jiongyu Yin ◽  
Weidou Ni
Keyword(s):  
Linear Regression ◽  
Municipal Solid Waste ◽  
Multiple Linear Regression ◽  
Solid Waste ◽  
Regression Method ◽  
Linear Regression Method ◽  
Waste Generation ◽  
Multiple Linear Regression Method ◽  
Solid Waste Generation

An application of QSRR approach and multiple linear regression method for lipophilicity assessment of flavonoids

2019 ◽  
Vol 164 ◽  
pp. 681-689 ◽  
Author(s):  
Mariusz Zapadka ◽  
Mateusz Kaczmarek ◽  
Bogumiła Kupcewicz ◽  
Przemysław Dekowski ◽  
Agata Walkowiak ◽  
...  
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Regression Method ◽  
Linear Regression Method ◽  
Multiple Linear Regression Method

scholarly journals Application of Modified Grey Forecasting Model to Predict the Municipal Solid Waste Generation using MLP and MLE

2021 ◽  
Vol 6 (5) ◽  
pp. 1276-1296
Author(s):  
Mohd Anjum ◽  
Sana Shahab ◽  
Mohammad Sarosh Umar
Keyword(s):  
Linear Regression ◽  
Municipal Solid Waste ◽  
Solid Waste ◽  
Likelihood Estimation ◽  
Grey Model ◽  
Waste Generation ◽  
Elementary Model ◽  
Grey Forecasting ◽  
Solid Waste Generation ◽  
Forecasting Theory

Grey forecasting theory is an approach to build a prediction model with limited data to produce better forecasting results. This forecasting theory has an elementary model, represented as the GM(1,1) model , characterized by the first-order differential equation of one variable. It has the potential for accurate and reliable forecasting without any statistical assumption. The research proposes a methodology to derive the modified GM(1,1) model with improved forecasting precision. The residual series is forecasted by the GM(1,1) model to modify the actual forecasted values. The study primarily addresses two fundamental issues: sign prediction of forecasted residual and the procedure for formulating the grey model. Accurate sign prediction is very complex, especially when the model lacks in data. The signs of forecasted residuals are determined using a multilayer perceptron to overcome this drawback. Generally, the elementary model is formulated conventionally, containing the parameters that cannot be calculated straightforward. Therefore, maximum likelihood estimation is incorporated in the modified model to resolve this drawback. Three statistical indicators, relative residual, posterior variance test, and absolute degree of grey indices, are evaluated to determine the model fitness and validation. Finally, an empirical study is performed using actual municipal solid waste generation data in Saudi Arabia, and forecasting accuracies are compared with the linear regression and original GM(1,1). The MAPEs of all models are rigorously examined and compared, and then it is obtained that the forecasting precision of GM(1,1) model , modified GM(1,1) model, and linear regression is 15.97%, 8.90%, and 27.90%, respectively. The experimental outcomes substantiate that the modified grey model is a more suitable forecasting approach than the other compared models.

scholarly journals Accident Prediction Model at Unsignalized Intersection Using Multiple Linear Regression Method

2017 ◽  
Vol 1 (2) ◽  
pp. 379-389
Author(s):  
N. K. Oghoyafedo ◽  
J. O. Ehiorobo ◽  
Ebuka Nwankwo
Keyword(s):  
Linear Regression ◽  
Prediction Model ◽  
Multiple Linear Regression ◽  
Regression Method ◽  
Linear Regression Method ◽  
Design Standards ◽  
Accident Prediction ◽  
Geometric Characteristics ◽  
Unsignalized Intersections ◽  
Multiple Linear Regression Method

The issue of road accidents is an increasing problem in developing countries. This could be due to increasing road traffic/vehicle occupancy, geometric characteristics and road way condition. The factors influencing accidents occurrence are to be analysed for remedies. The purpose of this research is to develop an accident prediction model as a measure for future study, aid planning phase preceding the designed intervention, enhance the production of updated design standards to enable practitioners design unsignalized intersection for optimal safety, reduce the number of accidents at unsignalized intersections. Five intersections were selected randomly within Benin City and traffic count carried out at these intersections as well as geometric characteristics and roadway conditions. The prediction model was developed using multiple linear regression method and the standard error of estimate was computed to show how close the observed value is to the regression line. The model was validated using coefficient of multiple determination. The establishment of the relationship between accidents and traffic flow site characteristics on the other hand would enable improvement to be more realistically accessed. This study will also enhance the production of updated design standards to enable practitioners design unsignalized intersection for optimal safety, reduce the number of accidents at unsignalized intersections.

scholarly journals THE EFFECT OF LEADERSHIP, JOB SATISFACTION AND ORGANIZATIONAL COMMITMENT ON EMPLOYEE PERFORMANCE AT RUMAH SAKIT UMUM DAERAH BESUKI SITUBONDO, INDONESIA

2018 ◽  
Vol 6 (6) ◽  
pp. 322-334
Author(s):  
Amrozi ◽  
Zarah Puspitaningtyas ◽  
Djoko Poernomo
Keyword(s):  
Job Satisfaction ◽  
Organizational Commitment ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Random Sampling ◽  
Employee Performance ◽  
Sampling Technique ◽  
Regression Method ◽  
Linear Regression Method ◽  
Multiple Linear Regression Method

This study is to examine the influence of leadership, job satisfaction and organizational commitment on employee performance. Population in this research was the entire employees of Rumah Sakit Umum Daerah (RSUD) Besuki, Situbondo, Indonesia which was about 295 peoples. Then, the researcher applied probability random sampling technique to select 170 respondents as the sampling. The researcher analyzed the data by applying multiple linear regression method. The result shows that leadership and job satisfaction contribute positive and significant effect on employee performance, while organizational commitment has no effect on employee performance.

scholarly journals Pengaruh Disiplin Kerja dan Pemberian Insentif terhadap Kinerja Karyawan PT Putra Karisma Palembang

2021 ◽  
Vol 2 (1) ◽  
pp. 25-42
Author(s):  
Andini Dwi Saputri ◽  
Susi Handayani ◽  
Muhammad Kurniawan DP
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Employee Performance ◽  
Regression Method ◽  
Linear Regression Method ◽  
Multiple Linear Regression Method ◽  
Sample Technique ◽  
Saturated Sample ◽  
Analyze Data

This study aims to analyze the effects of work discipline and incentives on the performance of employees of PT Putra Karisma Palembang. The sample was selected using the saturated sample technique. Data from 57 respondents were collected through interviews, documentation, and questionnaires. This study implemented the multiple linear regression method to analyze data. The results prove that partially each of work discipline and incentives has no significant effect on employee performance. However, simultaneously work discipline and incentives have a significant effect on employee performance. This insight is beneficial for PT Putra Karisma Palembang. To improve employees' performance, the company should consider both work discipline and incentives factors together.   Penelitian ini bertujuan untuk menganalisis pengaruh disiplin kerja dan pemberian insentif terhadap kinerja karyawan PT Putra Karisma Palembang. Sampel dipilih menggunakan teknik sampel jenuh. Data 57 responden dikumpulkan melalui wawancara, dokumentasi, dan kuesioner. Studi ini mengimplementasikan metode regresi linier berganda untuk menganalisis data. Hasil investigasi membuktikan bahwa secara parsial baik disiplin kerja maupun pemberian insentif masing-masing tidak berpengaruh signifikan terhadap kinerja karyawan. Tetapi, secara simultan disiplin kerja dan pemberian insentif berpengaruh signifikan terhadap kinerja karyawan. Fakta ini bermanfaat bagi PT Putra Karisma Palembang. Untuk meningkatkan kinerja karyawan, maka perusahaan harus mempertimbangkan faktor disiplin kerja dan pemberian insentif secara bersama-sama.

scholarly journals ANALYSIS OF FACTORS AFFECTING THE PRICE FLUCTUATION OF CAYENNE PEPPER IN MALANG REGENCY

2021 ◽  
Vol 5 (1) ◽  
pp. 19-26
Author(s):  
Nurul Laili ◽  
Sri Hindarti ◽  
Dwi Susilowati
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Research Method ◽  
Commodity Prices ◽  
Secondary Data ◽  
Regression Method ◽  
Linear Regression Method ◽  
Factors Affecting ◽  
Independent Variables ◽  
Multiple Linear Regression Method

 This study aims to 1) Analyze the pattern of changes in commodity prices for spanish pepper in Malang District. 2) Analyzing the factors that influence fluctuations in the price of spanish pepper in Malang District. The research method used is quantitative method that uses secondary data in the form of time series obtained from several related agencies, namely the Central Statistics Agency of Malang District, Department of Industry and Trade, and Department of food crops, horticulture, and plantation in Malang District. Analysis of the data used is multiple linear regression with the dependent variable is the price at the consumer level from 2009-2018, while the independent variables use the data of the price of spanish pepper at the producer level, the amount of production, and the amount of consumption from 2009-2018. The study found that: 1) The development of the price of spanish pepper had a trend that tended to increase during the last 10 years. 2) From the results of data processing using multiple linear regression method with Eviews 9.0 application, it is found that the factor that significantly influences changes in the price of spanish pepper is the price at the producer level, while the amount of production of spanish pepper and the number of requests does not significantly affect the change in spanish pepper prices in Malang District. 

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