TAILIEUCHUNG - Final Report of Artificial Neural Network

ất đai là tài nguyên của mỗi quốc gia vô cùng quý giá, là tư liệu sản xuất đặc biệt, là thành phần quan trọng hàng đầu của môi trường sống, là địa bàn phân bố các khu dân cư, xây dựng các cơ sở kinh tế, văn hóa, an ninh và quốc phòng. Việc quản lý sử dụng hiệu quả, bền vững tài nguyên đất là mục tiêu của mọi quốc gia. Vấn đề quản lý và sử dụng đất đai đã có những ảnh hưởng lớn đối với sự phát triển KTXH. Trong quản lý, sử dụng đất đai,. | The ANN is trained by the Pattern Recognizer (PR) module handles the running and training of the ANN. If a different behavior is desired, only the PR need be swapped out with a new supervisor which will train the ANN for the new purpose. To begin training, the weights of the connections in the ANN are initialized to pseudo-random values through the use of a 16-bit linear feedback shift register (LFSR). The ANN outputs a mean squared error (MSE), which is a measure of how close its outputs were to the training set. When the PR determines that the MSE is below a threshold value for all its training data sets, it concludes that the training is complete and signals ready for user input by lighting a green LED. This green LED is the indication of passing the Built-in Self-test (BIST). The ANN can be re-trained at any time in one of two ways: redo the initial training by resetting seed in the linear feedback shift register;or, retrain the LFSR seed and only resets the ANN which will result in a different set of initial weights and ultimately different ANN behavior.

• Báo cáo khoa học
• Artificial Neural Network
• data modeling tools
• Anrudimentary
• switches
• LCD screen
• non linear
• Journal of technology and science education
• Model detecting learning styles with artificial neural network
• Model detecting learning styles
• Singular Value Decomposition
• Latent Semantic Indexing
• International Journal of Computer Science & Communication Networks
• Design of intrusion detection system
• Artificial neural network and application of rough set
• Intrusions in a network
• Artificial neural network in textiles
• Biological nervous systems
• Process information
• Highly interconnected processing elements
• Building maintenance contractor
• Multi criteria decision making methods
• Artificial neural network model
• Spearman correlation coefficients
• Groundwater level
• Levenberg marquardt algorithm
• Groundwater level prediction
• Nuclear engineering and technology
• Radiation interaction position in plastic rod scintillators
• Fast and simple technique
• Position sensitive detector
• Artificial intelligence of particles in water management
• Data mining
• Swarms of particles in water management
• Prediction and planning in the management
• Numerical Model
• Storm surge
• Tropical cyclone
• Neural network models
• Electrical Energy Demand Forecasting
• Recurrent Neural Network
• Non linear factor
• Time series analysis
• Journal of Chemistry
• Heterogeneous Fenton
• Nanoporous clinoptilolite
• Neural network
• Artificial neural network (ANN)
• Multiple regression analysis
• Method development
• Artificial neural networks
• Mixture of ascorbic acid
• Solar irradiance forecasting
• Root mean square error
• Artificial neural networks via assessment
• Mean absolute error
• Bài giảng Máy học nâng cao
• Máy học nâng cao
• Bài giảng Máy học
• Backpropagation algorithm
• Elman neural network
• Recurrentneural network
• Groundwater level forecasting
• Simulation of groundwater level
• BMC Bioinformatics
• Gene regulatory networks
• Prediction of response
• Clinical trial
• Group Lasso
• Biological Neural Networks
• Artificial Neural
• Delta Rule
• The Backpropagation
• Hebbian Learning
• ANN representations
• Perceptron Training
• Multilayer networks
• Remarks on the Backpropagation algorithm
• Neural network application development
• Vietnam Journal of Science and Technology
• Water quality classification
• Dong Nai river
• Excellently water quality
• High order sliding mode control
• Anti sway based compensation
• Pso algorithm for overhead crane
• Leaf length
• Leaf width
• Leaf area
• Developing estimation models
• New switching controller
• Soft computing high accuracy implementation
• Generates the duty ratios
• Risk management
• Risk assessment
• Failure mode
• Effect Analysis
• Construction project
• Modeling of laser direct structuring process
• Optimization of laser direct structuring process
• Artificial neural network and response surface methodology
• Response surface methodology
• The MID products
• Response surface and artificial neural network prediction model
• Optimization for surface roughness in machining
• Optimization for surface roughness
• Response surface model
• ANN prediction model sufficiently predict