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The energy-saving gap of building is serious. In practical matters of building engineering, the input process of time-varying system can be divided into several stages. In every stage, the system has its own rules and features. At present, various evaluation methods are slow in solving this matter. Cascade neural network can properly describe the growth continuity of each part of building energy-saving...
Back Propagation (BP) neural network was optimized by Genetic Algorithm (GA) to be Genetic Algorithm Optimized Back Propagation (GA-BP) neural network. The data of Monte Carlo simulations was used to train BP neural network and GA-BP neural network. The accuracy of each neural network was investigated and compared. The result showed GA-BP neural network was much steady and more accurate. A laser source...
This paper presents a new diagnosis method for classifying current waveform events that are related to a variety of induction machine faults. The method is composed of two sequential processes: feature extraction and classification. The essence of the feature extraction is to project a faulty machine signal onto a low dimension time-frequency representation (TFR), which is deliberately designed for...
In this paper, the global asymptotic stability is investigated for a class of stochastic neural networks with time-varying delay and generalized activation functions. By constructing appropriate Lyapunov-Krasovskii functional, and employing the free-weighting matrix method and stochastic analysis technique, a delay-dependent criterion for checking the global asymptotic stability of the addressed neural...
Base bleed propellant is an important component of the increasing rang projectile using base bleed technology. Unsteady strongly combustion leads to extinguish, reignition or critical state which produce an effect on rang dispersion. The burning behavior is determined by the initial pressure of combustion chamber and the maximum pressure decay rate, which was investigated by simulation experimental...
The magnetic anomaly created by ferromagnetic ships may endanger their invisibility. Nowadays, a new technique called closed-loop degaussing system can reduce the magnetic anomaly especially permanent one in real-time. To achieve it, a model able to predict off-board magnetic field from onboard measurements is required. Many researchers settle the problem by some numerical models. In this paper, we...
Firstly, according to the Beijing urban rail transit network characteristics and based on the data of the historical passenger flow, the passenger flow in sections is distributed and the referenced passenger flow in sections is gotten on the theoretical basis of the shortest path distribution of static unbalanced distribution model. Then through a lot of BP neural network modeling experiments, a reasonable...
Snort is an open source network intrusion detection and prevention system (IDS/IPS) utilizing a rule-driven language, its shortcoming is unable to detect new attacks. This paper explores how to integrate Artificial Intelligence into Snort IDS/IPS, which enables IDS/IPS adapt to networks and detect anomalies. As for preprocessors of Snort IDS, a learning algorithm such as artificial neural network...
This paper presents an integration of S-Transform and Probabilistic Neural Network (PNN) technique for identifying the location of a switched capacitor causing a power quality problem. The transient caused by the capacitor switching is one of the important power quality (PQ) problems since it may adversely affect the system as well as sensitive loads. S-Transform has the ability to detect the disturbance...
The security of ferry shows the characteristics of dynamics, randomness and uncertainty, and the system of its security is a typical non-linear system. Due to the limitations of traditional mathematical methods solving the non-linear system, this paper applies the wavelet neural network model for safety evaluation based on the assessment index system and weight algorithm. Results prove that the wavelet...
By analysis of working principle of elastic steel plate type load moment limiter, the nonlinear relation between the load moment and the horizontal displacement of moment limiter is indicated. This paper proposes a soft-sensing model based on functional link neural network (FLNN) with the horizontal displacement of moment limiter as input and the load moment as output. The model can apply the single-layer...
High voltage submersible motor works in deep water all the year around, and its operating insulation performance deteriorates influenced by the complex environment. Due to the special installed circumstances, the motor can not be readily maintained. Because of the losses caused by motor deterioration, the prediction of the insulation life-expectancy has a great significance. This paper analyzes the...
This electronic For the limitations of dependence on previous experience and neural network forecasting model in current thunderstorm prediction. Considering the characteristics of the thunderstorm in Chongqing, the thunderstorm prediction model based on least square support vector machine (LS-SVM) is established. The data are preprocessed by principal component analysis(PCA) firstly. Then, the search...
In this paper, we evaluate realizations for implementing an RFID reflected electro-material signature (REMS) sensor. REMS sensors allow passive measurement, recording, and reading of environmental data such as temperature in a small, low cost device. This paper presents results from two configurations: a three-section lossless microstrip transmission line and a monopole probe inserted into a lossy...
The basic principle of Artificial Neural Networks and BP algorithm was introduced in this paper. The application of BP algorithm Artificial Neural Networks in fault diagnosis of 40TM liquid-gas hammer was studied. The superiority of BP algorithm Artificial Neural Networks in fault diagnosis was proved by the MATLAB simulation and the training. The causes of faults were determined by BP algorithm Artificial...
This paper introduces a method for the fault diagnosis of a rotor system. For a vibration signal of a rotor system fault, an AR model is established first, and then the related parameter and amplitude spectrum of this mode can be obtained, etc. The experiments show the above-mentioned method can effectively diagnose the fault of a rotor system.
Long range dependence is closely linked with self-similar stochastic processes and random fractals, which have been considered extensively for signal processing applications and computer network traffic modeling. The Hurst parameter captures the amount of long-range dependence in a time series. Typically, the analysis of self-similar series is performed using: the variance-time plot, the R/S plot,...
Incorporating knowledge from domain expert to a classifier is one of the techniques which require to be considered in solving imbalanced dataset problems. In this study, the proposed technique is a development to extend the process for imbalanced dataset where the individual classification system has already been designed for balanced data set. This paper introduces a methodology and preliminary results...
Recently, accidents such that seniors fall down from the bed in care facilities or hospitals are increased. To prevent these accidents, we have developed the awakening behavior detection system using Neural Network. In this paper, it is a problem that the detection success rate of the current system using captured image in the clinical site is not enough. So, we analyze the captured image in the clinical...
The technique of ice storage is the uppermost technical measure for the future in China, which can realize the “peak load shifting” and the Demand-Side Management, meliorate the contradictions between providing and demanding. Based on the ASHRAE (American Society of Heating, Refrigeration, and Air Conditioning Engineers) coefficient method and ANN (Artificial Neural Networks) method, the hourly temperature...
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