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A novel piecewise model for pHEMTs with accurate Ids and its first three derivatives (gm, gm2 and gm3) is presented. The entire operating region is divided into several subregions. Aiming at improving the model accuracy in each subregion, the conventional Angelov models are developed with different optimized parameters. To solve the problem of the discontinuity between adjacent subregions, the artificial...
Through the application of genetic algorithms (genetic algorithm, simplified as GA) and BP(Back Propation) neural network, I built a prediction model of roses diseases, in which I choose six indicators as the input of network, they are the minimum temperature, maximum temperature, average temperature, minimum humidity, maximum humidity, average humidity in the greenhouse, then I choose three diseases...
This study using computer image processing and artificial neural network sensor technologies constructs a method of identifying ice slurry density based on the value of ice color image. The method is applied to the Jinan section of the Yellow River through the ice image acquisition, R/G color extraction, network learning and training, the final output target value of ice or water, and the actual image...
With the e-commerce market competition becoming more and more furious, it has become one of the focuses of companies that how to avoid customer churn and carry out customer retention. This paper applies many techniques of data mining to the research of customer churn, such as clustering analysis, decision tree, neural network, etc, establishes an e-commerce customer churn model and analyzes the factors...
A new approach called dynamic programming field for modeling the robot environments is presented and it's beneficial to the path planning. The dynamic programming field, which is approximated by Neuro-Dynamic Programming, records environmental information through a neural network and can be used to compute the approximate optimal cost between any two points. Based on the dynamic programming field,...
This paper discussed and researched the structure and algorithm of fuzzy neural network controller based on the character of fuzzy logic and neural network theory. For the nonlinear system characteristics of uncertainty, high order and hysteresis, this paper used the fuzzy neural network technology to control nonlinear system and improved the control quality obviously. Take the single inverted pendulum...
A great deal of attentions is currently focused on multisensor data fusion. A very important aspect of it is track-to-track association and track fusion in distributed multisensor-multitarget environments. The approach based on Hopfield neural network has been developed. But the performance of this approach is limited because Hopfield neural network is often trapped in the local minima. This paper...
The paper presents three kinds of grey neural network combined model for short-term prediction of urban traffic parameters, which are parallel grey neural network, series grey neural network, and inlaid grey neural network. They are employed to forecast a real vehicle speed in Barbosa road of Macao with satisfied precision. The experiment shows that the above three kinds of mode are feasible and effective...
Data classification has been studied widely in the fields of Artificial Intelligence, Machine Learning, Data Mining and Pattern Recognition. Up to the present, the development of classification has made great achievements, and many kinds of classified technology and theory will continue to emerge. This paper discusses a great deal of classification algorithms based on the Artificial Neural Networks,...
Artificial neural networks(ANN) has being used widely in information processing, intelligence control because of its abilities of self-organization, self-learning and parallel-processing. The work to use ANN theory and Fuzzy sets together to solve the practical problem is being promoted with the fuzzy sets birth and development. Based on the basic theory of RBFNN and fuzzy sets, a new fuzzy discrimination...
This paper proposes a hunting control approach for multiple mobile robots with local sensing. Predator Robot (PR) requires the sensing information and makes decision without communication with other PRs. The cooperation may emerge by local interactions among the robots. The invader (IR) is given the intelligent ability to escape. Experiments results show the validity of the proposed approach.
Negotiation is an important activity most related to the decision-making process in the e-business. It involves the interaction between different parties and usually goes through a number of iterations. Similar to the negotiation process in the real world, software agent working in the virtual environment performs automated negotiation in this way. This paper proposes an agent-based learning method...
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