1、Stator optimization using artificial neural network
2、Number character recognition based on BP artificial neural network
3、The first modeling approach is artificial neural network (NN).
4、Adaptive dynamic power management model based on artificial neural network
5、Anti-mechanical problems in the study of artificial neural network;
6、The establishment of the BP artificial neural network and grey system united model and grey data pretreatment depends on BP artificial neural network interpolate.
7、Subsidence prediction model combining RS and ANN( artificial neural network) is estab1 ished.
8、Evaluation of competitive performance of construction companies based on artificial neural network;
9、Method: The artificial neural network of reverse transmission and absorbance subtraction technique were used.
10、Both logistic regression and artificial neural network (ANN) models were developed.
11、So artificial neural network is a dynamic system with highly non-lineal continued time.
12、Based on the explanation on principle of artificial neural network, the BP network model for reservoir operation rules is established.
13、Using artificial neural network to solve the questions about computer cryptology will be an important study field of neural network and will bring a new clew to cryptology.
14、A critical review on the potential application of artificial neural network in membrane fouling research is given, and the prospect of artificial neural network in membrane bioreactor is pointed out.
15、The expert system based on artificial neural network was used, and the constitutive equation of PRMMCs was built.
16、A fast method for spectrum analysis and interpolation using artificial neural network (NN) for the microwaves surveying system is studied.
17、Based on artificial neural network technology and PC technology, a dynamic estimation method of EAF electric parameters is presented.
18、An elementary discussion on city fire - risk evaluation by applying back - propagation algorithm of artificial neural network;
19、Analysis and simulation to the relation between rainfall and runoff in karst basin with artificial neural network model
20、Based on the powerful nonlinear reflection and training function of artificial neural networks, the model of BP neural network for foundation piles integrity testing is put forward.
21、Aim at data inspection and mode identification of atmospheric environment, B-P network evaluation mode was established by the application of artificial neural network theory.
22、Objective: to investigate the potential of learning vector quantization (LVQ) artificial neural network tools for discrimination and forecasting of occurrent intensity of typhoid and paratyphoid.
23、Based on the experimental modal data and artificial neural network method, the sway brace in the framework structure is identified in this paper.
24、This paper sets up the model of artificial neural network for acoustic direction finding systems of targets used in the battle field.
25、Second, the process of modeling an artificial neural network has very high automaticity, for it can accomplish many inner processes automatically.
26、The approach is based on negative selection mechanism of the natural immune system and combined with artificial neural network to be used for monitoring.
27、QoS routing based on artificial neural networks
28、This paper presents a kind of software faults prediction model based on artificial neural network and the structure of the feed-forward multi-layer network with backpropagation learning algorithm.
29、In an example, based on the characteristics of structure, function, environment adaptability and feature of system service, a artificial neural network simulation system was established to evaluate the healthiness grade of Quercus liaotungensis forest ecological system in Dongling mountain.
30、Based on the aforementioned work, the relative displacement change in storeys of the frame( RDCSF) is extracted as the damage characteristic parameter, and the structural damage detection is also analyzed by combining the design of artificial neural network.
