The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Reconfigurable manufacturing systems are susceptible to disturbances because of the characteristics associated with changeover of machine configuration and functionality. An Artificial Neural Network Driven Decision-Making System can mitigate these disturbances, if applied with extensive knowledge of the manufacturing system. This paper introduces a new concept into the paradigm of agile manufacturing...
A modified Hopfield Artificial Neural Network is proposed to solve effectively and efficiently Boolean Satisfiability (SAT) NP-hard problems. The proposed Neural Network is compared against other traditional methods employed in this field, such as Greedy SAT and Genetic Algorithms for SAT. The results show that the proposed network represents a good alternative given their output quality and response...
This paper presents an application of cognitive networking paradigm to the problem of inter-cell interference coordination (ICIC) in Long-Term Evolution-Uplink (LTE-UL). We describe state-of-the-art, research challenges involved, and a novel random neural network (RNN) based power controller and interference management framework. The RNN based cognitive engine (CE) learns how the electromagnetic environment...
This paper proposed a concept of the multi-agent neural network, where neurons are agents of the multi-agent system. Each agent has a decision-making system that rests upon the system of production rules. A multi-chromosome genetic algorithm was developed. This algorithm allows to train a multi-agent neural network simultaneously by several parameter classes of the target function. Efficiency of the...
We study on artificial neural network-based controllers which are either trained or evolved by using the supervised or unsupervised learning approach. We employed backpropagation for the supervised method and the genetic algorithm for the unsupervised method. After training the controllers, we applied the controllers to our three newly designed mini-3D games. We performed a comprehensive study on...
The nitrifying process (NP) is an important step in dinitrochlorobenzene production. This paper presented an intelligent optimization control system (IOCS) to implement the modeling, optimization, and control of the NP by improved back-propagation neural networks, c-means clustering, genetic and chaos approaches. The results of actual runs demonstrate the validity of the system.
In this paper we address the problem of modeling creativity in Artificial Intelligence using a Genetic or Evolutionary based approach to computing, where the universe of discourse is represented as theories or programs in an extension to the Logic Programming language, which makes possible to handle incomplete or even contradictory information in an evolutionary environment. Indeed, we present a new...
The dependable operation of brain-computer interfaces (BCI) based on electroencephalogram (EEG) signals requires precise classification of multi-channel EEG signals. The design of EEG interpretation and classifiers for BCI are open research questions whose difficulty stems from the need to extract complex spatial and temporal patterns from noisy multidimensional time series obtained from EEG measurements...
In the paper the method of creating investment strategies for a profitable trading system is described. This method is based on artificial intelligence techniques and technical analysis tools. Created strategies describe the investment signal and amount of cash or stocks, which should be used at a given moment. The carried out experiments allow to find values of parameters for generating investment...
Designing and implementing the decisions of non-player characters in first person shooter games becomes more difficult as the games get more complex. For every additional feature in a level potentially all decisions have to be revisited and another check made on this new feature. This leads to an explosion of the number of cases that have to be checked, which in its turn leads to situations where...
This paper presents an experiment of using neuronal networks as a pulse shape generator for CP-OFDM. A set of pulse shapes were generated using genetic algorithm that minimizes the mean square error of the timing offset estimator. These pulse shapes were used to train function approximation neural networks. Such neural networks make the use of adaptive pulse shaping in OFDM systems feasible. Results...
Short term load forecasting is essential to the operation of electricity companies. It enhances the energy-efficient and reliable operation of power system. artificial neural networks are employed for short term load forecasting owing to their powerful non-linear mapping capabilities. These are generally trained through backpropagation, genetic algorithm (GA), particle swarm optimization (PSO) and...
Since the Neural Network (NN) with a Genetic Algorithm (GA) as a complement; are good optimization tools, we compare its performance with the Response Surface Methodology (RSM) that is generally used in the optimization of the process, in this case welding process. For the data used in the comparison, the results show that NN plus GA and RSM have a good results and very well performance, for identify...
Most of the artificial neural networks (ANN) based applications are implemented on FPGAs using fixed-point arithmetic. The problem is to achieve a balance between the need for numeric precision, which is important for network accuracy, and the cost of logic areas, i.e. FPGA resources. In this paper we propose a genetic algorithm based methodology permitting the optimization of the FPGA resources needed...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.