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Query response time prediction is an important and challenging problem in database systems. Especially for applications which handle large amounts of data or where time loss and deadlocks are hardly tolerated, it is very useful to predict the query response times before actual execution. This paper aims to predict query response times automatically using neural network-based approaches, and compares...
Electroencephalogram (EEG) signal plays an important role in the field of brain-computer interface (BCI) which has diverse applications ranging from medicine to entertainment. BCI acquires brain signals, extracts informative features and translates these features into a control signal for an external device. The Purpose of this work is to select proper frequency band and to extract suitable features...
Wireless Ad Hoc Networks are capable of communication through wireless medium without the need for a pre-existing infrastructure. Much effort has gone into mobile ad-hoc network (MANET) research over the past decade. Yet, even today, mobile ad-hoc networking is seen as a relatively new area of research. The reason for this can be traced to the fact that the maturity in truly understanding these networks...
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...
The operation principles of proton exchange membrane (PEM) fuel cell system relate to thermodynamics, electrochemistry, hydrodynamics, mass transfer theory, which form a complex nonlinear system, and it is different to establish its mathematical model. This paper utilizes the approach and self-study ability of artificial neural network to build a model of nonlinear system, and adapts the modified...
The understanding of the physiological basis of basic functions of brains requires detailed information about the functional structures of neuronal networks. Feedback loops are crucial dynamic motifs playing a pivotal role in the regulation and control of many important physiological and biochemical processes such as gene transcription, signal transduction, and metabolism (intracellular processes),...
Automatic one-and three-phase re-closing power lines, after short circuit shutdown, is a very effective way to improve the reliability of power delivery. Re-closing while the fault is not cleared can be dangerous for some electrical appliances. To prevent re-closing of a short circuit a method allowing stable arc detection has developed. The method is based on the estimation of real-time parameters...
The ever increasing need for energy efficient systems has led to various ingenious ideas about energy management. A major offshoot of this search for energy efficient solutions is demand management in power systems. The goal of any demand management program is to control the demand for electric power among customers thereby creating load relief for electric utilities and improving system security...
Fuel cells are electrochemically complex, nonlinear, and dynamic energy conversion systems. Due to the dynamic characteristics of the fuel cell electrical performance models are used for system evaluation. In this study, Artificial Neural Network (ANN) technique is used as the modeling tool for internal structures of the fuel cells complex electrochemical reactions. The proton exchange membrane fuel...
The paper presents the two-stages adaptive approach for short-term forecast of parameters of expected operating conditions. The first stage involves decomposition of the time series into intrinsic modal functions and subsequent application of the Hilbert transform. During the second stage the computed modal functions and amplitudes are employed as input functions for artificial neural networks. Their...
BP neural network (back propagation neural network) is a mathematical model for machine learning. It has a strong advantage in terms of prediction of the future events, and taking into account the different applications, its impact factors are different, which makes the model complex and diverse. A general modeling approach is proposed, which creates and stores BP neural network model dynamically,...
Base on the situation analysis of copper matte smelting in P-S converter in the slag stage, this paper use modern BP neural network algorithm to realize the intelligent prediction of optimal flux addition through C programming. The module which is proved by the neural network toolbox of MATLAB can meet the demand of practical application. And the algorithm training time is greatly shortened in engineering...
This paper analyzed the enterprise process energy consumption systematically with a lot of statistic data starting from energy efficiency, and established the energy consumption prediction model based on genetic algorithm of wavelet neural network (GA-WNN). This paper made previous optimization training with genetic algorithm, which have feature of natural evolution regularity, to the weights and...
In consideration of the common sensor failures in aero-engine control system, a new approach is proposed using dual redundant predictors based on neutral network in this paper. The neutral network temporal redundant predictor and spatial redundant predictor are created over the time series redundant information of single sensor and the space redundant information of multi-sensor respectively. The...
The gray gradient co-occurrence matrix and BP neural network were presented about the issue of the recognition of oceanic internal waves in a MODIS remote sensing image. First, the gray gradient co-occurrence matrix was used to extract the texture features of internal waves. Second, the appropriate eigenvalues extracted were selected as components of the input vector of the BP neural network.. Third,...
This paper describes a refinement of wind speed prediction methods in order to enhance their accuracy for wind energy applications. Specifically, techniques used to downscale raw forecasts from numerical weather prediction models are investigated. Wind speed measurements from several surface meteorological stations are used to test the downscaling process. While classical downscaling methods require...
The prestressed loss of group anchor in rock slope increase with time, which leads to the compression belt of structure plane in group anchor area was weakened, deformation of rock surface toward the free surface direction increase gradually, as a result, the slope stability was drastically reduced. Based on the group anchor layout of the abutment rock slope of an arch dam, the anchor-hold monitoring...
Guard against financial risks, reduce bad loans, increase the ability to identity risk of commercial banks, the key is risk warning. In view of the increasing proportion of personal loans in banking business, it is particularly important to warning personal loans default risk. Commercial bank lending itself is a complex nonlinear system, using general linear theory is difficult to objectively reflect...
Power system static security assessment is one of the most important problems which relate power system secure-stable performance. Static security can be rapidly assessed using the artificial intelligence technology. This paper compares the advantages and disadvantages of Artificial Neural Network (ANN) and Support Vector Machines (SVM) and then selects the SVM algorithm. A new multi-classification...
This paper proposes a new algorithm to recognize the printed characters as part of the blob recognition modules of Optical Character Recognition systems. The algorithm uses a SVM classifier and Zernike moments for feature extraction. A comparison with another algorithm based on a five layer convolutional neural network is done. An analysis of the accuracy and the time needed to process one character...
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