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The photoelectric conversion efficiency of photovoltaic cells is mainly affected by two factors, two factors are the operating temperature of the photovoltaic cell and the irradiance of the sun. In order to improve the photoelectric conversion efficiency of photovoltaic cells, combining with the two factors that affect photoelectric conversion efficiency of photovoltaic cells and the merits and demerits...
Wavelet neural network has a slow convergence rate, weak global search capability and easy to search the search results to a minimum, while the genetic algorithm has a high degree of parallelism, randomness, adaptive search and global optimization. The wavelet neural network is transformed and transformed to obtain the discretized wavelet neural network. In this paper, the three-layer wavelet neural...
The influence of temperature, irradiance and shielding ratio on the output characteristic curve of photovoltaic cells was studied in this paper. In order to improve the photoelectric conversion efficiency of photovoltaic cells, combining three major factors that affect photovoltaic cells, a maximum power point tracking (MPPT) scheme based on large variation genetic algorithm was proposed. In this...
At present, the detection of mixing uniformity in glass furnace batching system is mainly realized by artificial detection. However, this method is time-consuming and laborious, and there are some risks. For the problem of mixing uniformity detection, the nonlinear relation between the actual weight value and the mixing uniformity is established by the BP neural network, which can predict the mixing...
It is of great significance to carry out cities' air quality forecasting work for the prevention of the air pollution in urban areas and to the improvement of the living environment of urban residents. The air quality index (AQI) is a dimensionless index that quantitatively describes the state of air quality. In this paper, the data of air quality in Lanzhou released by china air quality online monitoring...
Obesity is an increasingly prevalent metabolic disorder, which results in increased risk of various diseases. One such disease is the coronary artery disease, which is the most common type of heart disease. Coronary artery disease (CAD) leads to the blockage of the arteries, that supply blood to the heart muscles, due to the accumulation of cholesterol and other material called plaque on the inner...
In order to improve the power supply quality of sine wave inverter for small wind power system, a control method that combines BP neural network (BPNN) with genetic algorithm (GA) is proposed in this paper. The BPNN is optimized by means of the GA to avoid the BPNN falling into local optimum value, and the optimized BPNN can better control the power output of the designed sine wave inverter. Simulation...
Addressing the complexity and isolation of the blast furnace, field engineers generally operate the system according to their former experience. While stability and safety are the first priority, it is natural to see extra consumption of ores and fuels. Over the recent years, researchers have been searching for the optimal operation point within the blast furnace by mathematical methods that include...
Energy crisis and environmental pollution stimulate the rapid development of new energy electric vehicles. The state of charge(SOC) is a key parameter of power battery in application, so the accurate estimation is extremely important. Factors affecting the battery SOC are many and complicated, scholars have proposed many methods to estimate SOC, but still does not solve the accuracy and practicability...
In this paper, rough set, genetic algorithm and BP neural network are combined together in pattern recognition. The neural network, rough set, and genetic algorithms are described in details. The wine dada in UCI database is considered and is dealt with by the above combination approach. The result shows that the accuracy of pattern recognition is improved and the cost of input is decreased. The proposed...
Accurate prediction of the crude oil output decline rate is crucial to ensure the stability of oil field. This paper presents a new method that utilizes the neural networks optimized by Genetic Algorithm(GA) to dynamically predict the crude oil output decline rate. Firstly, choose the best weights for neural network by the GA's survival of the fittest mechanism. Next, learn the rules of production...
Biological system such as neural networks and genetic algorithms are adapted to improve the doctors experience for diagnosis of illnesses. This work is introduced an approach for diagnosing breast cancer via classifying a well-known WBCD dataset based on a hybrid neurogenetic system. The suggested approach showed a good behavior and excellent classification accuracy through the implementation of several...
The information of electricity demand forecasting is a base for energy generation enterprise to develop electricity supply system. The purpose of this study is to develop a monthly electricity forecasting model in order to predict electricity demand for energy management. The proposed approach to monthly electricity demand time series forecasting model, describes the trend of the electricity demand...
In this paper, we propose an improved Elman neural network model which contains a new feedback mechanism composed of a special external feedback we proposed and inherent internal feedback. In order to guarantee the generalization ability of the established model, we adopt Genetic Algorithm to optimize initial connection weights and number of hidden layer nodes at the same time. This kind of improved...
In view of the fact that the material thickness of grate cooler system is difficult to measure, we present a new method of modeling that takes advantage of genetic algorithm to optimize the BP neural network and has a contrast with the pure BP neural network. Simulation shows that the BP neural network model which is optimized by genetic algorithm has a small error. At the same time, it is more stable...
A smart city is emerging as an application of information and communication technologies to mitigate the problems generated by the urban population growth. One of the smart city solutions is to establish an efficient fleet management relating to the use of a fleet of vehicles (e.g., ambulances and police vehicles). The most basic function in a fleet management system is the real time vehicle tracking...
Despite the tremendous attention Unmanned Aerial Vehicles (UAVs) have received in recent years for applications in transportation, surveillance, agriculture, and search and rescue, as well as their possible enormous economic impact, UAVs are still banned from fully autonomous commercial flights. One of the main reasons for this is the safety of the flight. Traditionally, pilots control the aircraft...
Recently, performance of deep neural networks, especially convolutional neural networks (CNNs), has been drastically increased by elaborate network architectures, by new learning methods, and by GPU-based high-performance computation. However, there are still several difficult problems concerning back propagation, which include scheduling of learning rate and controlling locality of search (i.e.,...
Tension and gauge control interact each other intensively in tandem cold rolling process, making control ineffective and unstable. In order to improve the thickness of the strip and tension control accuracy, control system of tandem cold rolling is equipped with the decoupling control of tension and gauge. Applying the method of Neural Network Simple Adaptive Control based on Genetic Algorithm, we...
Following analyzing existing challenges in addressing the balance between exploration and exploitation encountered by evolutionary algorithms, this paper develops a Genetic Algorithm with speciation (GASP). It first incorporates a novel encoding scheme and recombination method for a balanced genetic divergence when locating global optima in complex applications, such as structural and dynamic design...
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