By Jianye Zhang, Peng Zhang
This booklet specializes in diverse features of flight info research, together with the fundamental ambitions, tools, and implementation concepts. As mass flight facts possesses the common features of time sequence, the time sequence research tools and their software for flight info were illustrated from numerous features, equivalent to info filtering, info extension, function optimization, similarity seek, development tracking, fault analysis, and parameter prediction, and so forth. An clever information-processing platform for flight information has been demonstrated to aid in airplane tracking, education evaluate and clinical upkeep. The ebook will function a reference source for individuals operating in aviation administration and upkeep, in addition to researchers and engineers within the fields of information research and information mining.
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Additional info for Time Series Analysis Methods and Applications for Flight Data
NÞ Vrj Á br þ hj ð2:25Þ r¼1 In the formula, Vrj stands for the connecting weight between the hidden layer and the output layer, br for the node value of the hidden layer, hj for the node threshold of the output layer, and cj for the node value of the output layer. The node output function of the hidden layer is br ¼ f m m X ! Wir Á ai þ Tr ðr ¼ 1; . ; uÞ ð2:26Þ i¼1 In the formula, Wir stands for the connecting weight between the input layer and the hidden layer, ai for the node value of the input layer, and Tr for the node threshold of the hidden layer.
UÞ ð2:26Þ i¼1 In the formula, Wir stands for the connecting weight between the input layer and the hidden layer, ai for the node value of the input layer, and Tr for the node threshold of the hidden layer. The action function f ðxÞ usually takes the form of the sigmoid function f ðxÞ ¼ ð1 þ eÀx ÞÀ1 . The learning process of the neural network is: While the neural network is learning, if the error between the value of the output layer and the expected value is larger than the permitted error, the network will adjust the connecting weight and the threshold of the nodes in the connecting layer.
46 2 Preprocessing of Flight Data 2. Coding, Evaluating, and Operator Designing of Self-Expanding Genetic Algorithm The operation, representation, and evaluation of self-expanding genetic algorithm include the following aspects: (1) Coding. Binary coding, a coding method most widely used in the genetic algorithm, is relatively simple and easy to understand. Although binary coded string will be very long while solving high-dimensional optimization problem, the length of flight data trouble sample itself is relatively limited and cannot be expanded inﬁnitely.
Time Series Analysis Methods and Applications for Flight Data by Jianye Zhang, Peng Zhang