Partial Linear Method for Background Harmonic Voltage Estimation

The linear regression method which will be influenced by fluctuations could only calculate constant background harmonic voltage. To make up the limitation, this paper studies partial linear method. The method expands fluctuant background harmonic voltage at a time in accordance with Taylor series. On the basis of least sum of square error, the objective function selected by the method considers the influence of weight and uses bandwidth control each size of weight. This method can calculate fluctuant background harmonic voltage accurately. A case study based on the IEEE 14-bus test system is conducted and the results indicate that fluctuant background harmonic voltage can be obtained effectively and accurately by the proposed method.

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Partial Linear Regression Method in the Application of the Accurate Calculation of PQDIF Harmonic Responsibility

Proceedings of the 2015 International Conference on Modeling, Simulation and Applied Mathematics ◽

10.2991/msam-15.2015.82 ◽

2015 ◽

Author(s):

Aiqiang Pan ◽

Xingang Yang ◽

Yijun Liu

Keyword(s):

Linear Regression ◽

Regression Method ◽

Linear Regression Method ◽

Accurate Calculation ◽

Partial Linear

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Statistical inference in the partial linear models with the double smoothing local linear regression method

Journal of Statistical Planning and Inference ◽

10.1016/j.jspi.2013.10.004 ◽

2014 ◽

Vol 146 ◽

pp. 102-112 ◽

Cited By ~ 4

Author(s):

Hua He ◽

Wan Tang ◽

Guoxin Zuo

Keyword(s):

Linear Regression ◽

Statistical Inference ◽

Linear Models ◽

Regression Method ◽

Local Linear Regression ◽

Linear Regression Method ◽

Local Linear ◽

Double Smoothing ◽

Partial Linear ◽

Partial Linear Models

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Forecasting Medicine Purchase Budget using Multiple Linear Regression Method: Case Study - For Ende Regency Health Office

Proceedings of the 2nd International Conference on Applied Science, Engineering and Social Sciences ◽

10.5220/0009880501860192 ◽

2019 ◽

Author(s):

Marianus Angelo Dasi Muda ◽

Achmad Affandi ◽

Yoyon Kusnendar Suprapto

Keyword(s):

Linear Regression ◽

Multiple Linear Regression ◽

Regression Method ◽

Linear Regression Method ◽

Multiple Linear Regression Method

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Rainfall Prediction in South-Eastern Part of Bangladesh by Linear Regression Method

International Journal of Emerging Research in Management and Technology ◽

10.23956/ijermt.v6i6.255 ◽

2018 ◽

Vol 6 (6) ◽

pp. 119

Author(s):

Mohammad Shohidul Islam ◽

Sultana Easmin Siddika ◽

S M Injamamul Haque Masum

Keyword(s):

Linear Regression ◽

Correlation Coefficients ◽

Rain Gauge ◽

Regression Method ◽

Linear Regression Method ◽

Climate Data ◽

Rainfall Forecasting ◽

Statistical Parameters ◽

Time Duration ◽

Rainfall Prediction

Rainfall forecasting is very challenging task for the meteorologists. Over the last few decades, several models have been utilized, attempting the successful analysing and forecasting of rainfall. Recorded climate data can play an important role in this regard. Long-time duration of recorded data can be able to provide better advancement of rainfall forecasting. This paper presents the utilization of statistical techniques, particularly linear regression method for modelling the rainfall prediction over Bangladesh. The rainfall data for a period of 11 years was obtained from Bangladesh Meteorological department (BMD), Dhaka i.e. that was surface-based rain gauge rainfall which was acquired from 08 weather stations over Bangladesh for the years of 2001-2011. The monthly and yearly rainfall was determined. In order to assess the accuracy of it some statistical parameters such as average, meridian, correlation coefficients and standard deviation were determined for all stations. The model prediction of rainfall was compared with true rainfall which was collected from rain gauge of different stations and it was found that the model rainfall prediction has given good results.

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An alternative model of the vibronic coupling in octahedral complexes

Collection of Czechoslovak Chemical Communications ◽

10.1135/cccc19881134 ◽

1988 ◽

Vol 53 (6) ◽

pp. 1134-1140

Author(s):

Martin Breza ◽

Peter Pelikán

Keyword(s):

Linear Regression ◽

Alternative Model ◽

Potential Surface ◽

Analytical Formula ◽

Coupling Model ◽

Regression Method ◽

Vibronic Coupling ◽

Linear Regression Method ◽

Active Systems ◽

Jahn Teller

It is suggested that for some transition metal hexahalo complexes, the Eg-(a1g + eg) vibronic coupling model is better suited than the classical T2g-(a1g + eg) model. For the former, alternative model, the potential constants in the analytical formula are evaluated from the numerical map of the adiabatic potential surface by using the linear regression method. The numerical values for 29 hexahalo complexes of the 1st row transition metals are obtained by the CNDO/2 method. Some interesting trends of parameters of such Jahn-Teller-active systems are disclosed.

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The Accuracy Assessment of Weapon System Using Grey Linear Regression Method

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.268-270.1809 ◽

2012 ◽

Vol 268-270 ◽

pp. 1809-1813

Author(s):

Dai Yu Zhang ◽

Bao Wei Song ◽

Zhou Quan Zhu

Keyword(s):

Linear Regression ◽

Fuzzy Theory ◽

Accuracy Assessment ◽

Regression Method ◽

Small Sample ◽

Easy Access ◽

Linear Regression Method ◽

Grey Theory ◽

Weapon System ◽

Complex Engineering

The accuracy assessment of weapon system is always a complex engineering. How to make the most of the information given in only a few tests and obtain reasonable estimate is always a problem. Based on the fuzzy theory and grey theory, a grey linear regression method is presented. From the numerical example, we can see that this method provides an easy access to deal with data in small sample case and may have potential use in the analysis of weapon performance.

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Perancangan Aplikasi Prediksi Jumlah Pendaftar Siswa Baru Dengan Metode Regresi Linier (Studi Kasus: SMA RK Deli Murni Bandar Baru)

Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) ◽

10.32672/jnkti.v3i3.2520 ◽

2020 ◽

Vol 3 (3) ◽

pp. 330-334

Author(s):

Novita Ria Lase ◽

Fristi Riandari

Keyword(s):

Linear Regression ◽

Regression Method ◽

Point Of View ◽

Computational Techniques ◽

Linear Regression Method ◽

Simple Linear Regression ◽

Tuition Fees ◽

Use Of Data ◽

New Students ◽

New Student

The problem of the SMA RK Deli Murni Bandar Baru school is to predict how many facilities that need to be provided for new students such as chairs, tables and others. This study discusses the prediction of the number of new student registrants at SMA RK Deli Murni Bandar Baru based on the amount of tuition fees using a simple linear regression method. From a commercial point of view, the use of data mining can be used to handle the explosion of data volumes, using computational techniques can be used to produce information needed which is an asset that can increase the competitiveness of an institution. Prediction is almost the same as classification and estimation, except that in the prediction the value of the results will be in the future. This system can be used to predict the number of applicants in the following year to help the school. The advantage is that this simple linear regression method is very simple so that it is easy to calculate and use. Saves the time needed to solve problems, especially those that are very complex.

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