Reliability of the electric grid structure for the transmission and distribution of power from the generating plants to the consumers, is an essential requirement for the reliability of electric supply. The components...
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ISBN:
(纸本)9781665403450
Reliability of the electric grid structure for the transmission and distribution of power from the generating plants to the consumers, is an essential requirement for the reliability of electric supply. The components of the grid is exposed to weather events which cause faults to the grid's structures. There is an expectation that as climate change alters the severity and number of weather events, electricity supplies and electricity grid reliability are expected to be affected. Computational intelligence models have been proven to be excellent predictive models for electricity reliability problems in previous studies. But there has not been sufficient literature reporting their applications in weather related electricity outage forecasting problems. In this study, weather related electricity outage was forecasted using artificial neural networks (ANNs) with hack-propagation algorithm. Real -life data sets of the city of Pietermaritzburg, South Africa, was used to investigate the performance of the ANN model and was compared with a conventional model exponential smoothing (ES). The Al model gave satisfactory results as compared to the ES model. The result is a demonstration of the robustness of computation techniques.
The C-130 aircraft is one of the most widely used medium transports in the world. It operates virtually everywhere, from the arctic circle to the Sahara. Operation in desert conditions, however, presents a challenge f...
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ISBN:
(纸本)9781728180175
The C-130 aircraft is one of the most widely used medium transports in the world. It operates virtually everywhere, from the arctic circle to the Sahara. Operation in desert conditions, however, presents a challenge for maintenance engineers regarding preventive maintenance scheduling. Erosion caused by sand particles drastically decreases turbine blades life. Recent studies showed that Artificial Neural Network ANN algorithms have much better capability at modeling reliability and predicting failure than conventional algorithms. In this study, more than thirty years of local operational field data were used for failure rate prediction and validation using several algorithms. These include Weibull regression modeling to establish a reference, feed-forward back-propagation ANN, and radial basis neural network algorithm. Comparison between the three methods is carried out. Results show that the failure rate predicted by both the feed-forward back-propagation artificial neural network model and radial basis neural network model are closer to actual failure data than he failure rate predicted by the Weibull model. The results also give an insight into the reliability of the engine turbine under actual operating conditions, which can be used by aircraft operators for assessing system and component failures and customizing the maintenance programs recommended by the manufacturer.
This paper presents an investigation on the performance of an active suspension system. After discussing a 4-DOF car suspension model, dynamic simulation of the system with an existing nonlinear classic controller cal...
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This paper presents an investigation on the performance of an active suspension system. After discussing a 4-DOF car suspension model, dynamic simulation of the system with an existing nonlinear classic controller called back-stepping method has been presented which had been previously introduced by Huang and Lin (2004). The model-based identification of the system is then preformed by the aid of the feed forward neural networks which are finally used for the corresponding fault detection process. Simulation results show that the proposed identification and fault detection approach is highly effective in evaluating the performance of an active suspension system.
In order to detect crop diseases and insect pests in crop cultivation timely and accurately and to determine which kind of diseases and insect pests,this paper uses some algorithms in the field of image processing and...
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In order to detect crop diseases and insect pests in crop cultivation timely and accurately and to determine which kind of diseases and insect pests,this paper uses some algorithms in the field of image processing and the prevailing neural network to identify crop diseases and insect *** order to better identify diseases and insect pests,this paper uses a variety of plant diseases and insect pests for analysis and research,then expands a variety of crop diseases and insect pests on the original basis,expands the practical field by modifying model parameters and other methods,which not only saves workload,but also saves a lot of time,and can be based on the ***-time conditions to make a better pest identification algorithm model.
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