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Given a large and complex network, we would like to find the best partition of this network into a small number of clusters. This question has been addressed in many different ways. Here we utilize the simulated annealing strategy to maximize the modularity of a network with our previous hard partitioning formulation for the community structure, which is based on the optimal prediction of a random...
Energy consumption forecast is an essential component in making energy plan. In the light of the complexity and nonlinearity of energy consumption system, the gray forecast model and neural network model are respectively established by using the energy consumption historical data of certain province. Then their advantages and disadvantages are analyzed. Lastly, the method of optimal combination is...
The instability disaster prediction model of tailings dam had been established, based on system analysis of the factors that caused the instability disaster of tailings dam, by selecting 6 prediction index, medium unit weight, cohesion, internal friction angle, slope angle, slope height and pore pressure ratio and combining with using theory of the rough set and neural network. First the rough set...
Grey model and support vector machine are fit for prediction in the small size of data, their advantages and disadvantages are probed in this paper at first. And then, the combined model is proposed, which combines grey model and support vector machine with optimal weights. The weights are obtained and optimized by minimizing the sum of squared residuals standard. Some experiments compared with grey...
By using the data of Shanghai's population age structure in 2004 2007, based on the forecasting model of Markov chain, the paper calculated the transition probability of the changes for population age structure in Shanghai. In the last, using the transition probability matrix predicted population age structure of Shanghai in the future. The conclusion is that: Aging trend is growing now and the next...
In order to predict gas content of coal seam accurately in binchang mining, we use core data to build the BP neural network. We select the important controlling factors which impacted gas content of coal seam, coal bed thickness, ash and max vitrinite reflectance as the basic features of the BP neural network model, and establish the BP neural network prediction model between coal bed methane content...
Efficient mapping of logical processes to physical processes is one of key technologies to accelerate parallel performance simulation. Aiming at minimizing the communications between SMP nodes and between host physical processes, this paper presents a novel method named TPsmp-LP3M. It automatically extracts communication pattern of logical processes from trace and then generates a two-phase mapping...
In order to realize safety prediction of workface stray current, it's important to confirm the characteristic indexes of workface stray current so as to insure the time margin and reliability of prediction. By analyzing the resistance distribution network of the system, the paper confirms the four parameters as follows to be the characteristic indexes of coalface stray current safety prediction: the...
This article firstly presents an analysis and survey regarding the traditional evaluation and forecasting model on fuzzy time series. lt is pointed out that the maximum Subordination degree method and Subordination degree-Weighted average method is not suitable to attribute space usually, and a new evaluation model is proposed. The empirical study show that the new evaluation model is better able...
A new prediction method combined variable weight Gray Verhulst model and gray integrated relation grade was proposed in this paper to solve the problem of power transformer fault prediction. Because power transformer gases concentration sequence was S-shaped, Gray Verhulst model was chosen to forecast the gases concentrations. Variable weight Gray Verhulst model was proposed based on 2 improved Gray...
The thesis introduces grey system model and RBF neural network. In the light of the drawbacks and merits of the two models, the author puts forward the residue amending combined prediction model, and makes a contrast between the three models in prediction and precision. The result indicates that, the combined model is better than that of the single models for higher precision and smaller error.
This paper focuses on space-time non-linear intelligent modeling for regional data, researches how to apply back-propagation neural network (BPN) into analysis of regional data. Thinking about sectional instability of spatial pattern, this paper divided space units of researching regions into different subregions by improved K-means algorithm based on spatial adjacency relationship. Then build a space-time...
One major problem in the management of the current large networks is the complexity and the enormous amount of operations required to satisfy user demands while using resources efficiently. In this study, we propose a network traffic forecasting strategy based on BP neural network (BP-NTF). First, we analyse the characteristics of network traffic and establish traffic forecasting methods based on...
Determining of vertical ultimate bearing capacity (VUBC) of concrete pile is very important to design and management of geotechnical engineering in soft soil area. However, it is not well solved because the VUBC increases with time after pile installation. In this paper, conventional model for time-VUBC relationships is introduced, and one new grey model is proposed to predict time-VUBC relationships...
A reliable and accurate short-term traffic forecasting system is crucial for the successful deployment of any intelligent transportation system. To address the complexity of real-world traffic forecasting conditions, this paper presents a layered traffic forecasting algorithm, which is implemented by a clustering neural network, Kohonen self-organizing map (KSOM) and four neural network paradigms...
The load forecast is the foundation of optium control for heating system. This paper systematicaly discussed the application research of heating system predication which adopted the fuzzy neural networks technology. RBF neural networks are constructed by MATLAB. This method is characterized by higher computing accuracy and fast convergence velocity, it is very suitable in the engineering and may greatly...
One of the most important reasons for poor performance on the basic education ICT projects is due to the lack of a systemic framework, which is used to identify the essential factors and their relationships during the project, the systemic framework is important especially for those cross-sector projects, such as the projects of ICT tests in Shanghai rural schools. Maturity Model frameworks were created...
Effectiveness forecast of especial vehicle is important in vehicle development and compare research. This paper establishes forecast model of vehicle effectiveness by factors analysis with interpretability, and RBF (radial basis function) neural networks with short training time and precise function. Secondly, the result of forecasted and original is contrasted together, then the quality and creditability...
This paper analysis the projection market diffusion process by Bass model, estimated the model parameters of projection market diffusion model. Use the past years projection purchase statistic data in China, make a positive analysis of projection diffusion model, forecast the purchases of future and prospect the time and number of maximum purchases.
In order to analyze the effect of typical public events on the urban traffic behaviors, this paper firstly studied the factors of traffic mode choice and their interaction at macroscopic and microcosmic angles. Then according to the traffic characteristic and scope of public events, a disaggregate model of traffic mode choice was set up. Finally, the model was applied in the case of split ratio forecast...
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