scholarly journals Corrigendum to “Fault Location of Active Distribution Networks Based on the Golden Section Method”

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Haizhu Yang ◽  
Xiangyang Liu ◽  
Yiming Guo ◽  
Peng Zhang
Keyword(s):  
Fault Location ◽  
Golden Section ◽  
Distribution Networks ◽  
Section Method ◽  
Golden Section Method ◽  
Active Distribution Networks

scholarly journals Fault Location of Active Distribution Networks Based on the Golden Section Method

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Haizhu Yang ◽  
Xiangyang Liu ◽  
Yiming Guo ◽  
Peng Zhang
Keyword(s):  
Fault Location ◽  
Golden Section ◽  
Flow Analysis ◽  
Energy Resource ◽  
Distribution Networks ◽  
Load Flow ◽  
Distributed Energy ◽  
Load Flow Analysis ◽  
Distributed Energy Resource ◽  
Golden Section Method

Aiming at the problem of fault location in distribution networks with distributed energy resources (DERs), a fault location method based on the concepts of minimum fault reactance and golden section is proposed in this paper. Considering the influence of distributed energy resource supply on fault point current in distribution networks, an improved trapezoidal iteration method is proposed for load flow analysis and fault current calculation. This method only needs to measure the synchronous current of the distributed energy resource and does not need to measure the voltage information. Therefore, the investment in equipment is reduced. Validation is made using the IEEE 34-node test feeder. The simulation results show that the method is suitable for fault location of distribution networks with multiple distributed generators. This method can accurately locate the faults of the active distribution network under different conditions.

ON THE ACCELERATION OF OPTIMIZATION METHODS FOR THE PROBLEM OF SYNTHESIS OF MULTILAYER OPTICAL COATINGS

2021 ◽  
Vol 6 ◽  
pp. 13-26
Author(s):  
Alexander Mitsa ◽  
◽  
Petr Stetsyuk ◽  
Alexander Levchuk ◽  
Vasily Petsko ◽  
...  
Keyword(s):  
Objective Function ◽  
Golden Section ◽  
Optical Coatings ◽  
Generalized Gradient ◽  
Arithmetic Operations ◽  
Section Method ◽  
Suffix Arrays ◽  
Multidimensional Search ◽  
Golden Section Method ◽  
Speed Up

Five ways to speed up the multidimensional search in order to solve the problem of synthesis of multilayer optical coatings by using the methods of zero and first orders have been considered. The first way is to use an analytical derivative for the target quality function of the multilayer coating. It allows us to calculate accurately (within the computer arithmetic) the value of the gradient of a smooth objective function and generalized gradient of a non-smooth objective one. The first way requires the same number of arithmetic operations as well as finite-difference methods of calculating the gradient and the generalized gradient. The second way is to use a speedy finding of the objective function gradient using the prefix- and suffix-arrays in the analytical method of calculating the gradient. This technique allows us to reduce the number of arithmetic operations thrice for large-scale problems. The third way is the use of tabulating the values of trigonometric functions to calculate the characteristic matrices. This technique reduces the execution time of multiplication operations of characteristic matrices ten times depending on the computer’s specifications. For some computer architectures, this advantage is more than 140 times. The fourth method is the use of the golden section method for the one-dimensional optimization in the problems of synthesis of optical coatings. In particular, when solving one partial problem it is shown that the ternary search method requires approximately 40% more time than the golden section method. The fifth way is to use the effective implementation of multiplication of two matrices. It lies in changing the order of the second and third cycles for the well-known method of multiplying two matrices and fixing in a common variable value of the element of the first matrix. This allows us to speed up significantly the multiplication operation of two matrices. For matrices having 1000 x 1000 dimension the acceleration is from 2 to 15 times, depending on the computer's specifications.

Focusing of Scattering Light by Improved Feedback Wavefront Shaping Technique Based on Golden Section Method

2017 ◽  
Vol 37 (6) ◽  
pp. 0626005
Author(s):  
胡显声 Hu Xiansheng ◽  
蒲继雄 Pu Jixiong ◽  
冀旋旋 Ji Xuanxuan ◽  
陈子阳 Chen Ziyang
Keyword(s):  
Golden Section ◽  
Section Method ◽  
Shaping Technique ◽  
Golden Section Method ◽  
Wavefront Shaping ◽  
Scattering Light

PARAMETER OPTIMIZATION OF SINGLE EXPONENTIAL SMOOTHING USING GOLDEN SECTION METHOD FOR GROCERIES FORECASTING

2019 ◽  
Vol 4 (2) ◽  
Author(s):  
Vivi Aida Fitria
Keyword(s):  
Golden Section ◽  
Exponential Smoothing ◽  
Food Prices ◽  
Percentage Error ◽  
Boundary Area ◽  
Section Method ◽  
Golden Section Method ◽  
Long Time ◽  
Exponential Smoothing Method ◽  
Single Exponential

Department of Agriculture and Food Security Malang City, especially in the Field of Food Supply Availability and Distribution requires a reference forecasting of food prices in Malang. The method used in the forecasting calculation is Single Exponential Smoothing. In the process of calculating the Single Exponential Smoothing method, it takes alpha parameters between 0 and 1. The problem is when to estimate the alpha value between 0 to 1 with trial error with the aim of producing minimal forecasting results. Therefore, this study aims to determine the optimal alpha value. The method used in this research is the Golden Section Method. The principle of Golden Section method in this study is to reduce the boundary area so as to produce a minimum MAPE (Mean Absolute Percentage Error) value The data used in this study is the price of 9 commodities of Groceries in Malang since January 1, 2016 until December 31, 2017. The results showed that the Golden Section method found that the optimal alpha value was 0.999 with MAPE average of 9 commodities is 0.79%. So with this golden section method researchers do not need a long time to determine alpha by trial error

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