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With the death of Moore's law, the computing community is in a period of exploration, focusing on novel computing devices, paradigms, and techniques for programming. The TENN-Lab group has developed a hardware/software co- design framework for this exploration, on which we perform research with three thrusts: (1) Devices for computing, such as memristors and biomimetic membranes. (2) Applications...
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...
The paper introduces the principle of traditional PID algorithm, analyzes its advantages and disadvantages, and proposes a new control scheme — variable structure fuzzy neural network for such a nonlinear and complex system of automatic Gauge control (AGC). Variable structure fuzzy neural network combines the advantages of neural network and fuzzy control, and also adds a genetic algorithm to optimize...
Deep neural networks enjoy high interest and have become the state-of-art methods in many fields of machine learning recently. Still, there is no easy way for a choice of network architecture. However, the choice of architecture can significantly influence the network performance. This work is the first step towards an automatic architecture design. We propose a genetic algorithm for an optimization...
The paper presents a deep analysis of the literature on the problems of optimization of parameters and the structure of the neural networks and the basic disadvantages that are present in the observed algorithms and methods. As a result, there are suggested a new algorithm for neural network structure optimization, which is devoided of the major shortcomings of other algorithms. The paper includes...
The paper proposes using a neuro-fuzzy controller in telecommunication networks for improving the routing process. An architecture of the neuro-fuzzy controller was developed. Linguistic variables, terms and membership functions for input and output values were defined. A rules base was developed. The operation of the neuro-fuzzy controller was simulated and trained.
A number of investigations were undertaken to enhance the behavior of high voltage outdoor insulators by adopting numerical methods of optimization, but no work is performed to account for the presence of pollution. In this paper, a shape optimization of a high voltage insulator is achieved with the objective of reducing the tangential electric field along its polluted surface by means of numerical...
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 this paper we explore the hybrid application of evolutionary computation and artificial neural networks in the development of intelligent systems able to solve the problem of approximating the optimal strategy in a tile-matching puzzle game. Three intelligent systems are proposed: an evolutionary heuristic technique, artificial neural networks, and a hybrid approach that combines both. Results...
The increasing amount of data to be processed coming from multiple sources, as in the case of sensor networks, and the need to cope with constraints of security and privacy, make necessary the use of computationally efficient techniques on simple and cheap hardware architectures often distributed in pervasive scenarios. Random Vector Functional-Link is a neural network model usually adopted for processing...
Smart City development centres around efficient resource management along with sustainable support to the environment. This paper presents methods for intelligent control of traffic lights for traffic management and resolving road congestion incidents. The increasing volume of traffic, along with ineffective management of road capacity, has contributed towards increasing number of congestion events...
Ozonation is one of the most important processes during drinking water treatment. To improve the efficiency of ozonation and to stabilize the quality of the treated water, the ozone dosage should be a good trade-off between the requirement of disinfection and the restriction of bromate formation. However, because of the changes of raw water quality and the nonlinear behavior of ozonation process,...
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...
The problem of Learning from Demonstration is targeted at learning to perform tasks based on observed examples. One approach to Learning from Demonstration is Inverse Reinforcement Learning, in which actions are observed to infer rewards. This work combines a feature-based state evaluation approach to Inverse Reinforcement Learning with neuroevolution, a paradigm for modifying neural networks based...
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