In predicting the reliability and failure of components, classical methods are often used by determining the distribution between failure times. Sometimes, the determination of this distribution does not always match the data pattern that is owned because of the limited data records and the many types of distribution that must be chosen. In addition, how much influence the time series has on components cannot be clearly analyzed. Therefore, in this study a prediction will be carried out by combining classical methods with machine learning, namely Support Vector Regression (SVR) and Least Square Support Vector Regression (LSSVR). Both methods are considered capable of improving the prediction accuracy of a series of data. The results showed that the classical combined method with LSSVR had better accuracy than SVR.
In this paper, we propose a new control-based the neural network and bootstrap method to get the predictive duty cycle for the maximum power point of hybrid Photovoltaic (PV) and Wind Turbine generator system (WTG) connected to 380 V grid. The neural network is designed to be controller by learning the data control of multi-input DC/ DC converter. The artificial neural network (ANN) needs many data for training then the ANN can give the predictive duty cycle to multi input DC/ DC converter. To get much data, we can use the bootstrap method to generate data from the real data. From Photovoltaic characteristic, we can get 344 real data after the data are made by bootstrap method we can get 8000 data. The 8000 data of PV can be used for training artificial neural network (ANN) of PV system. From wind turbine characteristic we can get 348 real data after the data are made by bootstrap method we can get 6000 data. The 6000 data of WT can be used for training artificial neural network of WT system. This new control has two responsibilities, are to shift the voltage of PV and WTG to optimum condition and to maintain the stability of grid system. From the simulation results those can be seen that the power of hybrid PV / WTG system using MPPT controller is in maximum power and has constant voltage and constant frequency of grid system.
The purpose of this study are to determine the extent of the gap between expectations and perceptions of Koperasi SHIPS Jawa Timur (KSJ) members, in this case KSJ is a Cooperative that both established and run using the Islamic Sharia. Besides, it aims to identify the service quality attributes that need to be considered in order to improve the quality of KSJ services. Questionnaire distribution was carried out based on the CARTER's dimensions (Compliance, Assurance, Reliability, Tangibles, Empathy, and Responsiveness). It was addressed to the KSJ members both employees and lecturers, resulting 67 respondents to be participated. Reliability and validity tests were conducted to validate the key constructs. The results indicated that the services provided to the KSJ members were still below the respondents' expectations. The biggest gap value was -1.67 in item P15 (Attractive appearance of the KSJ office and physical facilities). This means that the appearance of the office and supporting equipment of the KSJ was very much needed by the respondents, but in reality the KSJ has not been able to provide the appearance of the KSJ office in accordance with the respondents 'wishes and is still far from respondents' expectation.
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