scholarly journals Application of MARSplines Method for Failure Rate Prediction

2018 ◽  
Author(s):  
Małgorzata Kutyłowska
Keyword(s):  
Failure Rate ◽  
Basis Function ◽  
Water Pipes ◽  
Independent Variables ◽  
Rate Prediction ◽  
Final Note ◽  
Dependent Variables ◽  
Water Mains ◽  
Predicted Values ◽  
Model Failure

In this paper MARSplines method was presented to model failure rate of water pipes in years 2015-2016 in the selected Polish city. The output parameters were chosen as three dependent variables - three values of failure rate of water mains, distribution pipes and house connections. Diameter, season, material and kind of the conduit were selected as independent variables. At the beginning of modelling 21 basis (splines) function were assumed. On a final note two functions were selected (after reduction of negligible functions). The model consists of three factors: β0, β1 and β2. The penalty for adding basis function was assumed at the level of 2. The correlation was equalled to 0.44. Relatively huge discrepancies between real and predicted values of failure rate of water mains and house connections were observed. In the future investigations concerning this problem the three separated models for each kind of conduit should be created. The calculations using MARSplines method were carried out in the program Statistica 13.1.

scholarly journals K-Nearest Neighbours Method as a Tool for Failure Rate Prediction

2017 ◽  
Author(s):  
Małgorzata Kutyłowska
Keyword(s):  
Failure Rate ◽  
Euclidean Distance ◽  
Optimal Number ◽  
Distance Metrics ◽  
Optimal Prediction ◽  
Data Set ◽  
Independent Variables ◽  
Rate Prediction ◽  
Nearest Neighbours ◽  
Water Mains

The paper shows the results of failure rate prediction using non-parametric regression algorithm K-nearest neighbours. The whole data set for years 1999-2013 was divided randomly into two groups (learning – 75% and testing – 25%). Besides, data from year 2014 were used for verifying the model. The dependent variable (failure rate) was forecasted on the basis of independent variables (number of installed house connections, total length and number of damages of water mains, distribution pipes and house connections). Four types of distance metric: Euclidean, quadratic Euclidean, Manhattan and Czebyszew were checked and four KNN models were created. Taking into consideration all constraints and assumptions, models using Euclidean and quadratic Euclidean distance metrics gave the most optimal prediction results. The optimal number of K nearest neighbours equalled to 2 and 3 concerning models KNN-E, KNN-E2, KNN-C and KNN-M, respectively. Validation error was the smallest for models KNN-E and KNN-E2 and amounted to 0.0130, for model KNN-M was equal to 0.0152 and for KNN-C to 0.0150.

DEVELOPMENT AND EVALUATION OF MODIFIED RELEASE MATRIX TABLETS OF MILNACIPRAN HCL USING MELT GRANULATION TECHNIQUE

INDIAN DRUGS ◽  
2018 ◽  
Vol 55 (02) ◽  
pp. 68-71
Author(s):  
N. C Ratnakara ◽  
◽  
M. C. Gohel
Keyword(s):  
Drug Release ◽  
Matrix Tablets ◽  
Matrix Tablet ◽  
Modified Release ◽  
Independent Variables ◽  
Dependent Variables ◽  
Formulation Parameters ◽  
Predicted Values ◽  
Melt Granulation

The objective of the present study was to identify critical formulation parameters affecting the drug release from modified release wax matrix tablet of milnacipran hydrochloride employing the concept of design of experiments.The optimized amount of Compritol 888 ATO(intragranular) (X1), lactose (X2) and Compritol 888ATO (extragranular)(X3) were determined employing simplex latticedesign. The tablets were prepared using melt granulation technique. The in vitro drug release study was carried out in an acidic medium (pH 1.2) for 2 h and thereafter the dissolution study was conducted in phosphate buffer (pH 6.8).The selected dependent variables were the cumulative percentage of milnacipran hydrochloride dissolved at 1 (Y1), 8 (Y8), 16 (Y16) and 24 h (Y24). Mathematical models, correlating the independent variables with dependent variables were evolved. Optimization was performed for the three independent variables using the stated target ranges; Y1≤20%; Y8=45±5%; Y16=72±5%; Y24=100%. The optimized amounts of Compritol ATO888 (intragranular)(X1), lactose (X2) and Compritol 888ATO (extragranular)(X3), were found to be 60, 55 and 30 mg, respectively.The optimized formulation showed a release profile that was close to the predicted values. The drug was released by anomalous diffusion from the optimized formulation. Compritol 888ATO (intragranular) (X1), lactose (X2) and Compritol 888ATO(extragranular) (X3) were identified as critical variables.

scholarly journals MARSplines method as a tool for failure frequency modelling

2018 ◽  
Vol 44 ◽  
pp. 00086
Author(s):  
Małgorzata Kutyłowska
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Failure Rate ◽  
Basis Function ◽  
Adaptive Algorithm ◽  
Point Of View ◽  
Water Utility ◽  
Failure Frequency ◽  
Rate Prediction ◽  
Operational Data

The paper presents the results of failure rate prediction using adaptive algorithm MARSplines. This method could be defined as segmental and multiple linear regression. The range of segments defines the range of applicability of that methodology. On the basis of operational data received from Water Utility two separate models were created for distribution pipes and house connections. The calculations were carried out in the programme Statistica 13.1. Maximal number of basis function was equalled to 30; so-called pruning was used. Interaction level equalled to 1, the penalty for adding basis function amounted to 2, and the threshold – 0.0005. GCV error equalled to 0.0018 and 0.0253 as well as 0.0738 and 0.1058 for distribution pipes and house connections in learning and prognosis process, respectively. The prediction results in validation step were not satisfactory in relation to distribution pipes, because constant value of failure rate was observed. Concerning house connections, the forecasting was slightly better, but still the overestimation seems to be unacceptable from engineering point of view.

scholarly journals Prediction of Failure Frequency of Water-Pipe Network in the Selected City

2017 ◽  
Author(s):  
Małgorzata Kutyłowska
Keyword(s):  
Failure Rate ◽  
Failure Frequency ◽  
Input Signals ◽  
Water Mains ◽  
Output Neurons ◽  
Predicted Values ◽  
Hidden Layer ◽  
Water Meters ◽  
Quasi Newton ◽  
Operational Data

The paper presents the modelling results of failure rate of watermains, distribution pipes and house connections in one Polishcity. The prediction of failure frequency was performed usingartificial neural networks. Multilayer perceptron was chosen asthe most suitable for modelling purposes. Neural network architecturecontained 11 input signals (sale, production, consumptionand losses of water, number of water-meters, length andnumber of failures of water mains, distribution pipes and houseconnections). Three neurons (failure rates of three conduitstypes) were put to the output layer. One hidden layer, with hiddenneurons in the range 1-22, was used. Operating data fromyears 2005-2011 were used for training the network. Optimalmodel was verified using operational data from 2012. ModelMLP 11-10-3 was chosen as the best one for failure rate prediction.In this model hidden and output neurons were activatedby exponential function and the learning was done using quasi-Newton approach. During the learning process the correlation(R) and determination (R2) coefficients for water mains, distributionpipes and house connections equaled to 0.9921, 0.9842;0.8685, 0.7543 and 0.9945, 0.9891, respectively. The convergencesbetween real and predicted values seem to be, from engineeringpoint of view, satisfactory.

ANALISA PENGARUH IKLIM ORGANISASI DAN KOMPETENSI TERHADAP KINERJA PEGAWAI PT HUTAMA KARYA

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
Erik Wardhana, MM.
Keyword(s):  
Organizational Climate ◽  
Employee Performance ◽  
Sampling Technique ◽  
Simple Random Sampling ◽  
Free Variable ◽  
Independent Variables ◽  
Dependent Variables ◽  
Correlational Approach ◽  
Survey Research Methods ◽  
The Relationship

This study entitled "Analysis of Effect of Climate Organization and Competence Againt Employee PT. Hutama Karya ". The purpose of this study was to obtain information on the relationship between the free variable that organizational climate (X1) and competence (X2) with the dependent variable is employee performance (Y), either partially or simultaneously, This study used survey research methods with the correlational approach and predictive, which aims for the relationship and influence between independent and dependent variables. The sampling technique can be done randomly (simple random sampling) of 852 employees, which is considered to resprentatif is 89 people. And to solve problems, to analyze and examine the relationship and influence between the independent variables on the dependent variable used models kausalistik through regression analysis with SPSS 14.0

PENGARUH PERSONAL BACKGROUND, POLITICAL BACKGROUND DAN PENGEATAHUAN DEWAN TENTANG ANGGARAN TERHADAP PERAN DPRD DALAM PENGAWASAN KEUANGAN DAERAH

2008 ◽  
Author(s):  
Yesi Mutia Basri ◽  
Rosliana Rosliana
Keyword(s):  
Multivariate Analysis ◽  
Significant Influence ◽  
Political Activity ◽  
Primary Data ◽  
Financial Control ◽  
Independent Variables ◽  
Dependent Variables ◽  
Political Background ◽  
Activity Dependent

This research aim to examine the influence of personal background, political background, and council budget knowledge towards the role of DPRD on region financial control. This research is motivated by the fact that individual background will effect to individual behavior on political activity. Dependent variables in this research are personal background, political background, and council budges knowledge towards the role of DPRD on region financial control Independent variables are the role of DPRD on region financial control in planning, implementing, and responsibility steps. The data in this research consist of primary data that taken from questionnaires distributed directly to respondents. The collected are from 34 Respondents that members of DPRD at Pekanbaru. Hypothesis of this research are examine by using Multivariate Analysis of Variances (MANOVA). The result of this research HI personal background political background and budget knowledge have significant influence toward the role of DPRD on region financial control in planning steps.H2 personal background, politico I background and budget knowledge have no significant influence toward the role of DPRD on region financial control in Implementing steps. H3 personal background political background and budget knowledge have no significant influence toward the role of DPRD on region financial control in Controlling steps.

scholarly journals Weight Feedback-Based Harmonic MDG-Ensemble Model for Prediction of Traffic Accident Severity

2021 ◽  
Vol 11 (11) ◽  
pp. 5072
Author(s):  
Byung-Kook Koo ◽  
Ji-Won Baek ◽  
Kyung-Yong Chung
Keyword(s):  
Traffic Accidents ◽  
Average Rate ◽  
Modern Society ◽  
Rate Of Change ◽  
Weighted Voting ◽  
Independent Variables ◽  
Dependent Variables ◽  
Accident Severity ◽  
Harmonic Average ◽  
Bagging Method

Traffic accidents are emerging as a serious social problem in modern society but if the severity of an accident is quickly grasped, countermeasures can be organized efficiently. To solve this problem, the method proposed in this paper derives the MDG (Mean Decrease Gini) coefficient between variables to assess the severity of traffic accidents. Single models are designed to use coefficient, independent variables to determine and predict accident severity. The generated single models are fused using a weighted-voting-based bagging method ensemble to consider various characteristics and avoid overfitting. The variables used for predicting accidents are classified as dependent or independent and the variables that affect the severity of traffic accidents are predicted using the characteristics of causal relationships. Independent variables are classified as categorical and numerical variables. For this reason, a problem arises when the variation among dependent variables is imbalanced. Therefore, a harmonic average is applied to the weights to maintain the variables’ balance and determine the average rate of change. Through this, it is possible to establish objective criteria for determining the severity of traffic accidents, thereby improving reliability.

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