Neutral Network Algorithm Research Articles

Method Research on Data Assimilation for Burnup Distribution of PWR Based on Three=dimensional Variation and Neutral Network Algorithm

Method Research on Data Assimilation for Burnup Distribution of PWR Based on Three=dimensional Variation and Neutral Network Algorithm

Data assimilation for the burnup distribution applying the three-dimensional variational and artificial neutral network algorithm

In this paper, a data-assimilation method has been proposed and applied for the burnup distribution of PWR. The burnup distribution is significant for the safety and economy of the reactor, as it is essential for the fuel-reloading design and optimization. Due to the fact that the burnup distribution cannot be measured directly during the reactor operation, the numerical simulation is widely applied in reactor engineering. However, there definitely exist differences between the numerical simulation and the actual core due to some unavoidable factors, such as component manufacturing deviation, uneven flow distribution and so on. These differences would induce the errors to the simulation values of power distributions and hence to the burnup distributions. Therefore, a data-assimilation method for the burnup distribution has been proposed, aiming at reducing the burnup-distribution errors with application of the power-distribution measurements. In our research, the three-dimensional variational (3DVAR) algorithm was applied for burnup-distribution calibration and the artificial neutral network (ANN) algorithm was applied to establish the complex relations between burnup distribution and power distribution. As engineering verification, the proposed data-assimilation method has been applied to the CNP1000 PWR operated in China. The numerical results indicated that the burnup-distribution errors can be reduced notably, as the maximum value of relative errors for power distribution can be reduced from 9.53% to 5.11%.

Data Assimilation for the Burnup Distribution Applying the Three-Dimensional Variational and Artificial Neutral Network Algorithm

Data Assimilation for the Burnup Distribution Applying the Three-Dimensional Variational and Artificial Neutral Network Algorithm

Research on Investment Aid Decision of Transmission Line Project Based on Artificial Intelligent Technology

According to analyze the historical transmission line projects from 2016 to 2018, we screen out a series of key influencing factors by principal component analysis. Aimed at the accuracy of grid investment, this report constructs an artificial intelligent investment aid decision model based on neutral network algorithm to predict the construction cost of the transmission line project.

Origin identification of Chinese Maca using electronic nose coupled with GC-MS

Maca (Lepidium meyenii Walp.), originated in the high Andes of Peru, is rich in nutrients and phytochemicals. As a new resource food in China, Maca suffers marketing disorders due to the limitation of basic research. Due to the close relationship of Maca quality and origin of place, it’s of scientific, economic and social importance to set up a rapid, reliable and efficient method to identify Maca origin. In the present study, 303 Maca samples were collected from 101 villages of the main producing area in China. Using electronic nose and BP neutral network algorithm, a Maca odor database was set up to trace the origin. GC-MS was then employed to analyze the characteristic components qualitatively and semi-quantitatively. As a result, very significant differences (p < 0.01) were detected in the volatile components of Maca from different areas. This study not only constructs a network model to forecast the Maca origin, but also reveals the relationship between Maca odor fingerprints and origins.

Komparasi Algoritma Support Vector Machines dengan Algoritma Artificial Neural Network untuk Memprediksi Nilai Persetujuan Kredit Modal Kerja yang Diberikan Bank Umum

Credit may be meant money provision orcollection that can be equavalent with that, basedon credit approval or loan agreement between bankand other party who oblige lender to pay off thedebt after specific terms period with interestexpenses. Commercial Bank is a bank that operateits business in conventional and or based onsyariah principle which is in operation provide inand out payment service. In this business operation,commercial bank provides loan/credit facility to thecustomer in Rupiah and foreign currency. Workingcapital credit is a credit used to finnance workingcapital purposes are depleted in one or several timethe production. For example: to buy raw material,salary, rent a building, purchase merchandise andso forth. Working capital credit approval providedby commercial bank need to predict because it hasincreased of credit provision provided bycommercial bank that can be used as measurementof economic growth and country stability or asmeasurement of economic growth indicator frommonetary sector by Bank of Indonesia. In thisresearch will conducted working capital creditvalue approval prediction will be provided bycommercial bank using support vector machinealgorithm that is compared with artificial neutralnetwork algorithm. From the result of testing onsupport vector machine algorithm using kernel dotproviding the accuracy result : 68,8% and RMSE :11928,594 and the result acquired using artificialneutral network algorithm providing the accuracyresult : 84,7% and RMSE : 5806,350. This resultshows that the best performance for workingcapital credit value approval provided bycommercial bank is artificial neutral networkalgorithm.

Precipitation Retrieval Using 118.75-GHz and 183.31-GHz Channels From MWHTS on FY-3C Satellite

In this paper, the focus is on precipitation rate retrieval using 118.75 and 183.31-GHz channels from the microwave humidity and temperature sounder (MWHTS) onboard the FY-3C satellite. These channels provide not only atmospheric humidity profile measurements but they also provide temperature profile measurements. These measurements play important roles detecting and retrieving precipitation rates. Data from the MWHTS and the Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis (TMPA) 3B42 are matched in time and space. Matched datasets are used to verify precipitation detection algorithms and precipitation rate retrieval algorithms. To retrieve the precipitation rate, the multiple linear regression algorithm and back propagation (BP) neutral network algorithm are applied in the ten models proposed in this paper. After detailed retrieval analysis between these two algorithms, advanced algorithms are presented this paper to improve the accuracy of the precipitation rate retrieval. In our algorithms, the correlation coefficient of the precipitation rate over the ocean can reach 0.82, the bias is approximately 0.07 mm/hr, and the root mean square error (RMSe) is less than 0.4 mm/hr. Over land, the correlation coefficient is approximately 0.73, the bias is 0.1 mm/hr, and the RMSe is less than 0.5 mm/hr. These results show that our retrieval algorithms improve the retrieval accuracy. Moreover, we study a number of typhoons and find that the FY-3C MWHTS works well to retrieve typhoon precipitation rates. The potential sensitivities of the temperature and humidity channels are analyzed, which can improve the retrieval accuracy and lay the foundation for further research.

Application Research of Mathematical Economic Model in Terms of Gas Distribution and Reconstruction of Distribution Field in Coal Mine Stope

Research of the application on Mathematical Economic Model in Terms of Gas Distribution and Reconstruction of Distribution Field in Coal Mine Stope The research is divided into 2 sections, the first section is to analyze the application of mathematical economic model in coal mine stope gas distribution; The second section is to analyze the application of mathematic economic model in reconstruction of coal mine stope gas distribution field. From the perspective of mathematic economy, when there are a lot of data samples participating in distribution field reconstruction, the reconstruction based on neutral network algorithm is slightly superior to space information statistical approach. When there are a few data samples participating in reconstruction, the spatial system statistical approach is obviously superior to neutral network reconstruction approach in terms of reconstruction result. It is essential to choose coal mine stope gas distribution field reconstruction method scientifically so as to reduce occurrence of gas accident.

Improved Prediction of Michaelis Constants in CYP450-Mediated Reactions by Resilient Back Propagation Algorithm

In drug metabolism reactions, it has become increasingly important to measure Michaelis constants (Km), which are used for a variety of purposes, including identification of enzymes involved in drug metabolism, prediction of drug-drug interactions, etc. Cytochrome P450s (CYPs) comprise a super family of major human enzymes responsible for drug metabolism. Hence, computational prediction of Km in CYP-mediated reactions facilitates drug development in an efficient and economical way. In this study, we firstly constructed a large dataset of ten CYP isoforms associated with 169 binding substrates, and 210 experimental Km values in CYP-mediated reactions. To predict Km of substrates metabolized by various CYP isoforms, we developed a general prediction model by using resilient back-propagation neutral network algorithm, based on the structural and physicochemical properties of the substrates and the metabolic specificity of the enzymes. The predictive Km values achieve a squared cross-validation correlation coefficients (Q2) of 0.73 with the experimental values, which is better than that of the existing models. Moreover, our model can predict Kmvalues of the compounds metabolized by a wide range of CYP isoforms. This tool will be useful in large-scale drug screening studies for CYP enzymes and helpful in the drug design and development.

New pattern recognition system in the e-nose for Chinese spirit identification**Project supported by the National High Technology Research and Development Program of China (Grant No. 2013AA030901) and the Fundamental Research Funds for the Central Universities, China (Grant No. FRF-TP-14-120A2).

This paper presents a new pattern recognition system for Chinese spirit identification by using the polymer quartz piezoelectric crystal sensor based e-nose. The sensors are designed based on quartz crystal microbalance (QCM) principle, and they could capture different vibration frequency signal values for Chinese spirit identification. For each sensor in an 8-channel sensor array, seven characteristic values of the original vibration frequency signal values, i.e., average value (A), root-mean-square value (RMS), shape factor value (Sf), crest factor value (Cf), impulse factor value (If), clearance factor value (CLf), kurtosis factor value (Kv) are first extracted. Then the dimension of the characteristic values is reduced by the principle components analysis (PCA) method. Finally the back propagation (BP) neutral network algorithm is used to recognize Chinese spirits. The experimental results show that the recognition rate of six kinds of Chinese spirits is 93.33% and our proposed new pattern recognition system can identify Chinese spirits effectively.

The Study on Neutral Network Algorithm and Its Application to Fatigue Cracks Testing

The Study on Neutral Network Algorithm and Its Application to Fatigue Cracks Testing

Broadband complex permittivity determination using a two-port U-shaped coplanar waveguide with artificial neutral network algorithm

A two-port U-shaped Coplanar Waveguide (U-CPW) used for broadband complex permittivity measurement of high loss solutions is presented. Compared with the one-port measurement device, this two-port U-CPW coupled with artificial neural networks algorithm has the ability of reducing the multiple-solutions. Also, the measured T/R (transmission/reflection) coefficients were used instead of simulated reflection coefficients for training the neural networks that enhanced the accuracy of measurement results. Two real-valued neural networks associated with the U-CPW are used to reconstruct the two parts of the complex permittivity separately from the measured T/R coefficients. First, a large number of measured T/R coefficients of broadband frequency points of ethanol-water mixtures along with their theoretical complex permittivity are used to train two separate neural networks. Second, the trained networks are employed to reconstruct the complex permittivity of other solutions using the measured T/R coefficients. Compared with the results of Cole-Cole equation, the reconstructed results of methanol-water mixtures and ethanol-methanol mixtures at different volume fractions have been obtained with sufficient degree of accuracy in the frequency range 1-3 GHz at 20 ◦ C. For predicted values using the developed artificial neural network (ANN) architecture and those obtained from literature, the average relative errors of real and imaginary parts of complex permittivity are 2.27% and 2.12%, respectively.

Development of Adaptive Distance Relay for STATCOM Connected Transmission Line with Wavelet Transform and ANN

A new scheme to enhance the solution of the problems associated with Transmission line protection with Statcom connected is presentedin this paper.Static Synchronous Compensator (STATCOM) is a shunt type FACTS device connected at the midpoint of the transmission line to maintain the voltage atdesired level by injecting/absorbing the reactive power. This connection affects the performance of distance protection relay during line faults. Thefault detectionis carried out byusingenergy of the detail coefficients of the phase signals and artificial neutral network algorithm used for fault distance location for all thetypes of faults for transmission line. For each type of fault separate neural network is prepared for finding out the fault location.

Development of adaptive distance relay for statcom connected 220 kv transmission line with wavelet transform and ANN

A new scheme to enhance the solution of the problems associated with Transmission line protection with Statcom connected is presented in this paper. Static Synchronous Compensator (STATCOM) is a shunt type FACTS device connected at the midpoint of the transmission line to maintain the voltage at desired level by injecting/absorbing the reactive power. This connection affects the performance of distance protection relay during line faults. The fault detection is carried out by using energy of the detail coefficients of the phase signals and artificial neutral network algorithm used for fault distance location for all the types of faults for 220 kv transmission line. For each type of fault separate neural network is prepared for finding out the fault location. An improved performance is obtained once the neutral network is trained suitably, thus performance correctly when faced with different system parameters and conditions.

Fault Phase Selection and Distance Location Based on ANN and S-transform for Transmission Line in Triangle Network

This pape presents artificial neutral network algorithm for fault type classification and fault distance location for all the types of faults for transmission line in triangle network. This technology uses only one end data and accurate fault distance location fault type identifying is achieved after half cycle from the inception of fault. The proposed Artificial Neutral Network (ANN) based fault distance locator and fault distance locator uses transient energy which are extracted by S-transform. An improved performance is obtained once the neutral network is trained suitably, thus performance correctly when faced with different system parameters and conditions i.e. varying fault type, fault location, fault resistance, fault inception angle.

Application study of complex control algorithm for regenerative furnace temperature

Alternative switch combustion mode of air and gas is adopted on the two sides of the regenerative furnace, its temperature is in uncontrolled state in the switching process and the switch period is generally 3 ∼ 5 min. Thus, the conventional bi-cross limited combustion control method is no longer applicable to the object. This paper makes use of neutral network algorithm to adjust the static operating point. On this basis, fuzzy control strategy is used for the furnace temperature control. The actual application result shows that the control strategy is effective to solve the problem of the combustion control for regenerative furnace.