scholarly journals A fixed functional set genetic algorithm (FFSGA) approach for function approximation

2006 ◽  
Vol 8 (3) ◽  
pp. 193-206 ◽  
Author(s):  
Mohammad Tufail ◽  
Lindell E. Ormsbee
Keyword(s):  
Genetic Algorithm ◽  
Friction Factor ◽  
Linear Regression Analysis ◽  
Turbulent Pipe Flow ◽  
Decision Variable ◽  
Data Set ◽  
Functional Formulation ◽  
Effective Manner ◽  
Least Squares Optimization ◽  
Moody Diagram

This paper describes a simple mathematical technique that uses a genetic algorithm and least squares optimization to obtain a functional approximation (or computer program) for a given data set. Such an optimal functional form is derived from a pre-defined general functional formulation by selecting optimal coefficients, decision variable functions, and mathematical operators. In the past, functional approximations have routinely been obtained through the use of linear and non-linear regression analysis. More recent methods include the use of genetic algorithms and genetic programming. An example application based on a data set extracted from the commonly used Moody diagram has been used to demonstrate the utility of the proposed method. The purpose of the application was to determine an explicit expression for friction factor and to compare its performance to other available techniques. The example application results in the development of closed form expressions that can be used for evaluating the friction factor for turbulent pipe flow. These expressions compete well in accuracy with other known methods, validating the promise of the proposed method in identifying useful functions for physical processes in a very effective manner. The proposed method is simple to implement and has the ability to generate simple and compact explicit expressions for a given response function.

Pengaruh Penghargaan Terhadap Kinerja Karyawan pada CV. Dino Manunggal Karsa Bogor

2019 ◽  
Vol 4 (2) ◽  
pp. 17
Author(s):  
Dedy Mulyadi ◽  
Didik Purwanto
Keyword(s):  
Linear Regression ◽  
Performance Assessment ◽  
Correlation Coefficient ◽  
Linear Regression Analysis ◽  
Strong Relationship ◽  
Simple Linear Regression ◽  
New Employees ◽  
Company Policy ◽  
Effective Manner ◽  
Relationship Of

The question of compensation in addition to sensitive to be driving someone to worl due to an effect on morale and discipline employees. Therefore , any  agency or any organization should be able to provide compensation equal to the workload  to create a workforce that efficient and effective manner can be realized. Amaore than that, the company’s goal to improve performance. Performance assessment is a subjective process that involves human judgments. Thus, performance assessment is very likely wrong and very easily influonced by sources that are not actual, so it must be taken into account and considered reasinable. Frformance appraisals are considered  to meet the target if it has a good impact on new employees who rated their performance. Simple linear regression analysis using SPSS version 12:00 data processing obtained tegression equation Y = 0,487 X 74 + with an explanation of X = award, 74 = constant, 0.487 = coefficient awards, and Y = performance based on simple linear regression equation in case of increase of one unit of the  performance award will be increased 0.487 units. If company policy negates the performance award will remain at a constant rate (74) units . (A) Test results obtained thitung significant constants of (12.574) > t table for (1.960 then reject Ho constanta significant meaning. (B) significant Test award coefficient t count the results obtained by (2.164)> t table foe (1.96) then reject Ho the mean coeffent of appreciation affect the performance . (C) correlation coefficient analysis is done by calculating the product moment corration (pearson)  to test  whether or not a strong  relationship between the variables X  dan Y , based on the results of cakculations with SPSS  table valuse obtained by calculating the  correlation coefficient r (0.3100> r on the table for a = 0,05 (0.291) then reject Ho, which means there is a relationship of respect for performance. When we enter these valuse in the table shows the interpretation of the correlation coefficient between the interval from 0.20 to 0.399 which has a low relationship

PENGARUH CITRA MEREK DAN KUALITAS BENIH TERHADAP KEPUTUSAN PEMBELIAN PADA PT.PRABU ARGO MANDIRI (Studi Kasus Penjualan Benih Tomat Merk Maya di Purwkarta)

2017 ◽  
Vol 6 (2) ◽  
Author(s):  
Ahmad Iskandar
Keyword(s):  
Product Quality ◽  
Brand Image ◽  
Hypothesis Test ◽  
Descriptive Analysis ◽  
Linear Regression Analysis ◽  
Coefficient Of Determination ◽  
Decision Variable ◽  
Purchasing Decisions ◽  
Business World

In the era of globalization, the competition in the business world becomes very tight. Companies vying to be able to continue to compete and survive in the business world. Each consumer must have had the expectation that the products they buy are able to provide satisfaction for them to be making purchasing decisions. Consumer purchasing decisions of companies to seeds virtual brand still low due to the brand image and quality of seeds that are still unsatisfactory.This study aims to determine the responses of respondents regarding brand image, product quality, purchasing decisions and how big an impact on the brand image itself against purchase decisions on the PT. Prabu Argo Mandiri Bandung and how much influence the quality of products on the purchase decision.The method by which the samples is Simple Random Sampling consists of 80 respondents. The method of analysis in this research using descriptive analysis and verification which is composed of multiple linear regression analysis. Product moment correlation analysis, and the coefficient of determination used to measure the level of influence of brand image and product quality on purchasing decisions.The results based on descriptive analysis of brand image variable is in good enough category, variable quality of the product is in the unfavorable category, and the purchase decision variable is in the unfavorable category. The results based on correlation test showed that the brand image is partially significant effect on purchasing decisions by 68% and the product quality is partially significant effect on purchasing decisions by 13%. Hypothesis test results suggested that the increased purchasing decisions partially and simultaneously influence through brand image and product quality.

scholarly journals Acceleration Feature Extraction of Human Body Based on Wearable Devices

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 924
Author(s):  
Zhenzhen Huang ◽  
Qiang Niu ◽  
Ilsun You ◽  
Giovanni Pau
Keyword(s):  
Genetic Algorithm ◽  
Feature Extraction ◽  
Kalman Filter ◽  
Human Body ◽  
Wearable Devices ◽  
Human Motion ◽  
Data Set ◽  
Feature Extraction Method ◽  
Motion Data ◽  
Kalman Filter Algorithm

Wearable devices used for human body monitoring has broad applications in smart home, sports, security and other fields. Wearable devices provide an extremely convenient way to collect a large amount of human motion data. In this paper, the human body acceleration feature extraction method based on wearable devices is studied. Firstly, Butterworth filter is used to filter the data. Then, in order to ensure the extracted feature value more accurately, it is necessary to remove the abnormal data in the source. This paper combines Kalman filter algorithm with a genetic algorithm and use the genetic algorithm to code the parameters of the Kalman filter algorithm. We use Standard Deviation (SD), Interval of Peaks (IoP) and Difference between Adjacent Peaks and Troughs (DAPT) to analyze seven kinds of acceleration. At last, SisFall data set, which is a globally available data set for study and experiments, is used for experiments to verify the effectiveness of our method. Based on simulation results, we can conclude that our method can distinguish different activity clearly.

scholarly journals Osmotically inactive sodium and potassium storage: lessons learned from the Edelman and Boling data

2016 ◽  
Vol 311 (3) ◽  
pp. F539-F547 ◽  
Author(s):  
Minhtri K. Nguyen ◽  
Dai-Scott Nguyen ◽  
Minh-Kevin Nguyen
Keyword(s):  
Linear Regression ◽  
Measurement Errors ◽  
Linear Regression Analysis ◽  
Sodium Concentration ◽  
Lessons Learned ◽  
Dynamic Changes ◽  
Data Set ◽  
Storage Pool ◽  
Total Body ◽  
Sodium And Potassium

Because changes in the plasma water sodium concentration ([Na+]pw) are clinically due to changes in the mass balance of Na+, K+, and H2O, the analysis and treatment of the dysnatremias are dependent on the validity of the Edelman equation in defining the quantitative interrelationship between the [Na+]pw and the total exchangeable sodium (Nae), total exchangeable potassium (Ke), and total body water (TBW) (Edelman IS, Leibman J, O'Meara MP, Birkenfeld LW. J Clin Invest 37: 1236–1256, 1958): [Na+]pw = 1.11(Nae + Ke)/TBW − 25.6. The interrelationship between [Na+]pw and Nae, Ke, and TBW in the Edelman equation is empirically determined by accounting for measurement errors in all of these variables. In contrast, linear regression analysis of the same data set using [Na+]pw as the dependent variable yields the following equation: [Na+]pw = 0.93(Nae + Ke)/TBW + 1.37. Moreover, based on the study by Boling et al. (Boling EA, Lipkind JB. 18: 943–949, 1963), the [Na+]pw is related to the Nae, Ke, and TBW by the following linear regression equation: [Na+]pw = 0.487(Nae + Ke)/TBW + 71.54. The disparities between the slope and y-intercept of these three equations are unknown. In this mathematical analysis, we demonstrate that the disparities between the slope and y-intercept in these three equations can be explained by how the osmotically inactive Na+ and K+ storage pool is quantitatively accounted for. Our analysis also indicates that the osmotically inactive Na+ and K+ storage pool is dynamically regulated and that changes in the [Na+]pw can be predicted based on changes in the Nae, Ke, and TBW despite dynamic changes in the osmotically inactive Na+ and K+ storage pool.

An Improved Ant Colony Optimization Algorithm for Solving the TSP Problem

2010 ◽  
Vol 26-28 ◽  
pp. 620-624 ◽  
Author(s):  
Zhan Wei Du ◽  
Yong Jian Yang ◽  
Yong Xiong Sun ◽  
Chi Jun Zhang ◽  
Tuan Liang Li
Keyword(s):  
Genetic Algorithm ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Convergence Time ◽  
Ant Colony Optimization Algorithm ◽  
Data Set ◽  
Research Attention ◽  
Simply Supported ◽  
Source Data

This paper presents a modified Ant Colony Algorithm(ACA) called route-update ant colony algorithm(RUACA). The research attention is focused on improving the computational efficiency in the TSP problem. A new impact factor is introduced and proved to be effective for reducing the convergence time in the RUACA performance. In order to assess the RUACA performance, a simply supported data set of cities, which was taken as the source data in previous research using traditional ACA and genetic algorithm(GA), is chosen as a benchmark case study. Comparing with the ACA and GA results, it is shown that the presented RUACA has successfully solved the TSP problem. The results of the proposed algorithm are found to be satisfactory.

Heat Transfer in Turbulent Pipe Flow for Liquids Having a Temperature-Dependent Viscosity

1978 ◽  
Vol 100 (2) ◽  
pp. 224-229 ◽  
Author(s):  
O. T. Hanna ◽  
O. C. Sandall
Keyword(s):  
Heat Transfer ◽  
Friction Factor ◽  
Pipe Flow ◽  
Turbulent Pipe Flow ◽  
Fluid Viscosity ◽  
Temperature Dependent ◽  
Temperature Dependent Viscosity ◽  
Analytical Approximations ◽  
Constant Viscosity ◽  
Dependent Viscosity

Analytical approximations are developed to predict the effect of a temperature-dependent viscosity on convective heat transfer through liquids in fully developed turbulent pipe flow. The analysis expresses the heat transfer coefficient ratio for variable to constant viscosity in terms of the friction factor ratio for variable to constant viscosity, Tw, Tb, and a fluid viscosity-temperature parameter β. The results are independent of any particular eddy diffusivity distribution. The formulas developed here represent an analytical approximation to the model developed by Goldmann. These approximations are in good agreement with numerical solutions of the model nonlinear differential equation. To compare the results of these calculations with experimental data, a knowledge of the effect of variable viscosity on the friction factor is required. When available correlations for the friction factor are used, the results given here are seen to agree well with experimental heat transfer coefficients over a considerable range of μw/μb.

scholarly journals Method for the identification of explicit polynomial formulae for the friction in turbulent pipe flow

1999 ◽  
Vol 1 (2) ◽  
pp. 115-126 ◽  
Author(s):  
J. W. Davidson ◽  
D. Savic ◽  
G. A. Walters
Keyword(s):  
Least Squares ◽  
Symbolic Regression ◽  
Regression Method ◽  
Turbulent Pipe Flow ◽  
Model Complexity ◽  
Improve Performance ◽  
Rule Based ◽  
Least Squares Optimization ◽  
Starting Solutions ◽  
Crossover And Mutation

The paper describes a new regression method for creating polynomial models. The method combines numerical and symbolic regression. Genetic programming finds the form of polynomial expressions, and least squares optimization finds the values for the constants in the expressions. The incorporation of least squares optimization within symbolic regression is made possible by a rule-based component that algebraically transforms expressions to equivalent forms that are suitable for least squares optimization. The paper describes new operators of crossover and mutation that improve performance, and a new method for creating starting solutions that avoids the problem of under-determined functions. An example application demonstrates the trade-off between model complexity and accuracy of a set of approximator functions created for the Colebrook–White formula.

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