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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...
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...
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...
This paper presents the self-tuning PID parameters by applying Artificial intelligence(AI) algorithm for tuning the Brush DC motor. This proposed approach combines with two algorithms, so called the NN-GA, which are the Neural Network (NN) and the Genetic algorithm(GA). To show the effectiveness of the designed approach, the simulation results are then given. In addition, the simulation results are...
This paper presents a performance comparison of feedback linearization and field oriented control for a synchronous reluctance machine. In order to represent realistic drive performance and dynamics, look-up tables of the machine inductances as a function of currents are used to include saturation effect. Additionally, a trained neural network was implemented to take the nonlinear behavior of the...
In the process of establishing evaluation index system of physical education, the traditional methods setting weights for each indicator mainly include analytic hierarchy process, fuzzy comprehensive evaluation method, and Delphi method, etc. These methods mostly rely on experience, which is strongly influenced by artificial factors and cannot be avoided. Because artificial neural network model has...
VANETs are network of vehicle which is formed dynamically for short duration. Due to this they are susceptible to various types of attacks. This paper discusses the recent techniques used to counter various types of attacks that threaten the VANET. Researchers have proposed many solutions to solve these problems. This paper discusses all the most relevant solutions and analyzed them according to various...
In this paper, the method of improving the performance of permanent magnet synchronous motor in the presence of disturbance and friction is studied. First, collected data are used to train BP neural network to get an accurate friction model. Friction model is used to compensate the friction. Considering the influence of friction over-compensation or less-compensation and external disturbance, the...
This paper considers the comparison performance and effectiveness of the PID controller auto-tuning for brushless DC motor (BLDC motor) by applying artificial intelligence (AI) algorithm and the classical method of PID parameters tuning. Neural network algorithm (NN) and genetic algorithm (GA) are among the well-known artificial intelligences algorithm existing todays while the classical method is...
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 paper presents a real-time algorithm to compute the switching angles to control a three-phase multilevel cascaded inverter in order to minimize the THD to improve the EMC of the system. In particular, the proposed method uses an Artificial Neural network, trained by the GA algorithm, to identify the optimal switching angles corresponding to several values of DC sources voltage levels and the modulation...
Outlier detection has been used to detect the outlier and, where appropriate, eliminate outliers from various types of data. It has vital applications in the field of fraud detection, network robustness analysis, Insider Trading Detection, email spam detection, Medical and Public Health Outlier Detection, Industrial Damage Detection, Image processing fraud detection, marketing, network sensors and...
Automatic character recognition of handwritten numerals and characters has been an active subject of research due to its importance on industrial as well as educational platform. The off-line handwritten character recognition is an active area for research towards the new techniques that would help to improve recognition accuracy. Now a day's looking forward for rapidly growing technologies, with...
Recently, more neuroscience researches focus on the role of dendritic structure during the neural computation. Inspired by the specified topologies of numerous dendritic trees, we proposed a single neural model with a particular dendritic structure. The dendrites are composed of several branches, and these branches correspond to three distributions in coordinate, which are used to classify the training...
Fuzzy clustering is an alternative method to conventional or hard clustering algorithms, which makes partitions of data containing similar subjects. The tendency of adopting machine learning, big data science, cloud computation in various industries depends on unsupervised learning on data structures to tell the story about consumers' behavior, fraud detection, and market segmentation. Fuzzy clustering...
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...
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...
Because of rare earth futures stock variability and uncertainty of the market, many investors hope to be able to predict the price of rare earth futures on the stock market in the future. The neural network does do better than others in short-term forecasting, and there is no need to establish a complex nonlinear mathematical model and relationship. Based on these advantages, this paper uses the neural...
Camera calibration is necessary in machine vision application field. Calibration model has nonlinear characteristics, and establishment of mathematical model is often a complicated process, but neural network can solve the complex nonlinear problem effectively, neural network has strong nonlinear approximation ability, adaptive network parameters and fast learning. This paper presents a neurocalibration...
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