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How to operate a BFG/coal co-firing boiler in high efficiency is challenging for a gas/solid multi-fuel combustion system. Taking operation data from a real boiler, this study proposes an operation optimization strategy of BFG/coal co-firing boiler based on deep learning. Firstly, the thermal efficiency model is constructed based on deep learning with all the actual sampling data, which outperform...
This paper presented a method of evaluating the health of lithium battery based on the continuous hidden Markov model (CHMM). This paper focuses on how to use CHMM to build the evaluation model. The capacity of battery is chosen as the observation variable. The evaluation process is divided into two phases: leaning phase and evaluation phase. First, learning data is used to estimate the elements of...
Based on the actual data analysis, it is found in this paper that the supplementary air flow rate in the CDQ operation didn't follow the variation of the discharge rate of incandescent coke well, which results in the concentration increase of combustible gas in the exhaust gas and the decrease of economic efficiency. The correlation analysis results show that the introduced derived variables are more...
To help telecommunications operators accurately predict the terminal replacement behavior, and improve the success rate of marketing and the accuracy of resources devoting, huge user consumption data are used to build Deep Belief Network. The deep features that characterize the terminal replacement behavior are learned, through which a terminal replacement prediction model is conducted. Experiments...
This paper presents a data-driven adaptive soft sensor approach to investigate the performance and optimal operation of cooling tower for energy conservation. To achieve this aim, first, the cooling tower process is characterized by an adaptive soft sensor with nonnegative garrote (NNG) variable selection procedure. Then, based on the statistics result of NNG variable selection, the effect of environment...
In 20th century and in early 21st century, there were some massive earthquakes happened in China. Rapid and accurate estimation and assessment of casualties caused by earthquake is essential basis for government and administrators to initialize the appropriate level of emergent plan. In this paper, a casualty prediction system for earthquake based on geographic information system has been developed...
Elman neural network (ENN) is one of the well-known dynamic recurrent neural networks. A new self-adaptive particle swarm optimization (SPSO) was proposed to improve Elman in order to solve problems of dynamic prediction in this paper. SPSO combines ENN and form SPSONN hybrid algorithm. Based on the algorithm, a nonlinear time-varying model was established to prediction deformation of deep foundation...
A new optimized grey system model is presented to solve the modeling problems of 5-Axis CNC machine tool thermal error such as how to cope with the multiple influence factors, complicated develop trend. This model uses the Genetic Algorithm to optimized the new grey system model's dimensions of modeling message and the added coefficient of model's background value generating, and this method can improve...
Because the predictive models do not match the practical process, the traditional predictive functional control could not acquire better performance. Through real-time database acquires the process parameters, the characteristic model of process can be obtained using the identification method. The characteristic model, as the predictive model of predictive functional control, downlink the control...
Audible noise produced by corona discharges is one of the more important considerations in the design of UHV AC transmission lines, which will greatly affect the electromagnetic environment and the technical economical index of transmission lines, etc. So it will be of very important practical significance that making scientific researches on AN prediction from UHV AC transmission lines. Based on...
In order to deal with the complicated network video data, the work focuses on the technologies of multilayer semantic mining and proxy cache for streaming media. Semantic mining method based on network parameter is presented. Quadratic regression popularity prediction model is introduced to analyze current popularity of streaming media. And then cache replacement strategy based on semantic mining...
There are internal and external reasons for the occurrence of landslip. Through the analysis on a large number of investigation materials of landslip, the growth inducements of landslip are found out. By use of theories in blur maths, we conduct order arrangement of these inducements in accordance their significance, put forward blur judgment rule of landslip estimation and present applicable examples.
In this paper, conditions and methods of ARMA model's establishment and prediction were detailed analyzed, which were based on correlation characteristics of sample failure data. Because model parameters getting from moment estimation (ME) was very rough to small sample, particle swarm optimization (PSO) algorithm was used in maximum likelihood estimation (MLE) to obtain optimal numerical solutions...
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