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With the development of coastal region in Tianjin Binhai new district, environmental pollution, exhaustion of resources and ecological hazards are aggravated continuously. So for efficient utilization of resources and realization of sustainable development, study on the carrying capacity assessment of coastal region is the key means for guiding the management. This paper presents a Data-Driven Model...
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 paper proposed an artificial neural network (ANN) approach based on Lagrangian multiplier method (Lagrangian ANN) to solve the problem of economic load flow in a power system. Operational requirements and transmission losses are also taken care by the proposed approach. Power plant operating costs are represented by exponential cost functions. Simulation on a test example with six generating...
Aiming at the disadvantages of prediction model of single BP neural network, a prediction model was presented by combining AdaBoost algorithm and BP neural network for improving the forecasting accuracy of single BP neural network. A new updating method is proposed for the characters of ensemble BP neural network based on AdaBoost. The new method can update the model effectively and overcome the disadvantage...
Solar energy is a green energy which is not only perennial but also accessible to every strata of the world. An easy way to convert solar energy into electric energy is to use Solar Photovoltaic (SPV) system. Solar panel is a power source having nonlinear internal resistance. As the intensity of light falling on the panel varies, its voltage as well as its internal resistance varies. To extract maximum...
The goal of this paper is the consideration of the solving of visual attention on the based of winner-take-all neural networks. Selective tuning and Mozer model of visual attention are considered here. Also limitations, advances and open problems are shown.
This paper presents a neural network method for solving a class of linear fractional optimization problems with linear equality constraints. The proposed neural network model have the following two properties. First, it is demonstrated that the set of optima to the problems coincides with the set of equilibria of the neural network models which means the proposed model is complete. Second, it is also...
Inflation is one of the most important macroeconomic variables. However, the behavior of inflation is so complicated that both economists and statisticians have strived to model and forecast inflation for years. In this study, the linear AS-AD model and nonlinear artificial neural network (ANN) technique are both employed to have a better understanding of the inflation behavior in China from 1992...
Gross Domestic Product (GDP) is a benchmark for economic production conditions of a country. Estimates of economic growth in the coming year in a country has important roles, among others as a benchmark in determining business plans for business entities, and the basis for devising government fiscal policy. Artificial Neural Network (ANN) has been increasingly recognized as a good forecasting tool...
Artificial Neural Networks (ANN) has the characteristics of adaptive, self-organization and self-learning. It can obtain the capabilities such as classify knowledge, pattern discrimination and associative memory by training and learning. The Mining-induced geological hazards assessment can be viewed as a pattern recognition problem. In this paper, a mine geological hazard assessment model is proposed...
Using a dynamical model of happiness in humans, proposed in, we develop a model of happiness for a network of people using dynamical elements with interconnecting coupling factors. The network model of happiness is derived from a leader-followers network model proposed by Wang and Slotine. Such networks with interconnected dynamical elements can be found in sensor networks, electro-mechanical and...
Nonparametric Linear Regression and Artificial Neural Network models have been developed based on different perspectives and assumptions. In this paper a survey is made to compare the predictive performances of the nonparametric models of closing prices of Stock Index data, where the data is non normal. Comparative studies with the existing statistical prediction models indicate that the proposed...
Determining of the torpedo's service year reasonably, it is an effective way to reduce the military expenses expenditure, and forecast the torpedo economic life. We can forecast the data of exponential use maintenance cost by using the grey metabolism GM(1,1) model. In order to improve the prediction precision, the data was divided into several groups, and prediction residual was modified by using...
Gray-box neural models mix differential equations, which act as white boxes, and neural networks, used as black boxes, to complete the phenomenological model. These models have been used in different researches proving their efficacy. The aim of this work is to show the training of the gray-box model through indirect back propagation and Levenberg-Marquardt. The gray-box neural model was tested in...
Field-programmable gate arrays (FPGAs) can provide an efficient programmable resource for implementing hardware-based spiking neural networks (SNN). In this paper we present a hardware-software design that makes it possible to simulate large-scale (2 million neurons) biologically plausible SNNs on an FPGA-based system. We have chosen three SNN models from the various models available in the literature,...
The paper studies the application of principal component analysis and ANN (Artificial Neural Networks) for pre-warning of enterprise financial crisis, analyzes the factors of financial crisis, and constructs the model of the enterprise financial crisis with principal component analysis and ANN. It integrates simplifying of enterprise financial crisis index, dynamic learning of financial crisis knowledge...
Customer value is the value that based on customer's perceived value, which is a comprehensive comparison between perceived benefit and perceived cost. There are closely relationship of customer value and enterprise performance. The improvement of customer value contribute to enterprise performance. Based on the above theoretical analysis, the customer value was divided into 3 types that is "good",...
This paper introduces the use of the concept of small signal analysis, commonly used in circuit design, for understanding neural models. We show that neural models, varying in complexity from Hodgkin-Huxley to Integrate and fire have similar small signal models when their corresponding differential equations are close to the same bifurcation with respect to input current. The small signal model allows...
The crude oil demand is growing rapidly in China, driven by its rapid industrialization and motorization. China has already become the second-largest oil importer nation in the world, after the United States. The dynamic GM(1,1) model of grey theory is used to develop the dynamic GM(M,N) model to forecast the crude oil consumption and production in China. In order to improve the forecasting accuracy,...
In order to satisfy the needs of human resources management and development, this study took R&D professionals as the research object and proposed an evaluation model for high-tech enterprise human resources based on artificial neural network, then trained and tested the neutral network for personnel evaluation. And the network was improved to be very effective to stimulate the evaluation of human...
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