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Cryptography based on block ciphers use Key-dependent ciphers for encryption and decryption. The efficiency of these systems depends on the security and the speed of the algorithm. The encryption process needs to be adaptive and dynamic in order to face any cryptanalytic attacks. Increasing the complexity of the algorithm is one way to prevent the attacks. The introduced complexity increases the execution...
TSP (Travelling Salesman Problem) is a typical issue of combinatorial optimization problem in the domain of mathematics, which aims at finding the shortest pathway among the given cities, and visit each city only once. This essay introduces an efficient way to solve TSP based on virtual instrument technology, combining the genetic algorithm and annealing algorithm. Because it takes the advantage of...
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...
The aim of automatic multi-document abstractive summarization is to create a compressed version of the source text and preserves the salient information. Existing graph based summarization methods treat sentence as bag of words, rely on content similarity measure and did not consider semantic relationships between sentences. These methods may fail in determining redundant sentences that are semantically...
Artificial neural networks (NNs) are traditionally designed with distinctly defined layers (input layer, hidden layers, output layer) and accordingly network design techniques and training algorithms are based on this concept of strictly defined layers. In this paper, a new approach to designing neural networks is presented. The structure of the proposed NN is not strictly defined (each neuron may...
Power sector is facing a major issue in meeting the increasing power demand due to the unavailability of resources to meet the demand using conventional sources. Thus, the demand for renewable resources has increased. The prime energy resources in use are wind energy and solar energy. Solar energy is the most promising energy source since it is the most abundant energy source. In order to obtain maximum...
In this paper we use the popular card game Dominion as a complex test-bed for the generation of interesting and balanced game rules. Dominion is a trading-card-like game where each card type represents a different game mechanic. Each playthrough only features ten different cards, the selection of which can form a new game each time. We compare and analyse three different agents that are capable of...
In this study we aim to develop a decision support application for predicting ICU mortality risk that starts with a clinical analysis of the problem that also leverages machine learning to help create an algorithm with good performance characteristics. By starting from a clear basis in clinical practice we hope to improve algorithm development and the transparency of the resulting system. We start...
A new method that the hidden nodes of the neural network are chosen by the genetic algorithm is proposed in this paper. The experimental results show that the appropriate hidden nodes can be selected by the genetic algorithm, and the results from the identification indicate that the system is quite efficient for identifying multi-objective polluted infrared spectra.
This study proposes an intelligent real-time odor monitoring system for monitoring odor problems, a new type of environmental problems, in real-time and for managing harmful substances. This system minimizes the measurement error of individual sensors by building a gas sensor array integrating 8 sensors, and applies a pattern recognition algorithm revised for accurate data analysis. The revised pattern...
by using the characteristics of global optimization of GA and local optimization of BP neural network, the calculation accuracy and convergence rate of the traditional BP neural network are improved. Then a special performance forecasting model for shot put based on GA-BP is established. The numerical results show that the mean square errors, the mean absolute value of calculation and prediction are...
BP algorithm can be applied in comprehensive evaluation. A hybrid neural network based on the combination of GA and BP algorithms is proposed. The algorithm made fully use of GA's global searching to improve the learning ability of BP neural network. Then, the method is used in comprehensive evaluation, which the genetic algorithm can improve the weights of the neural network and enhance the training...
Distributed power generation is a small-scale power generation technology that provides electric power at a site closer to customers than the central generating stations. The Distributed Generation (DG) has been created a challenge and an opportunity for developing various novel technologies in power generation. The proposed work discusses the primary factors that have lead to an increasing interest...
This paper established a back propagation (BP) neural network tandem cold rolling force prediction model, and optimized by genetic particle swarm algorithm (GPSA). Genetic particle swarm algorithm has the advantage of both genetic algorithm (GA) and particle swarm algorithm (PSO) algorithm, integrates global searching ability with high convergence speed. Taking neural network weights and threshold...
Based on the investigation and statistics of the preparatory tunnel data in Chengchao Iron Mine, using the adjustable parameters adaptive genetic algorithm with combining hierarchical structure to optimize structure and solve parameters of the radial base function neural network(ACHG-RBF), the algorithm had trained and predicted the network and optimized the network topology. In addition, it has enhanced...
In order to deal with the defects of the poor convergences and easily immerging in partial minimum frequently, a new algorithm is proposed based on the combination of genetic algorithm and BP neural network, which is called GA- BP algorithm. This algorithm is applied to optimization of initial weights of BP Network, the structure and learn rule. It searches through the total solution space and can...
A high rate of expression of Endothelin protein in the placental cell is very much regulated by inhalation of tobacco smoke and leads to placental abnormalities subjected to birth failure. Our application developed using Image Processing, Nearest Neighbor algorithm (NN) and Genetic Algorithms (GA), automates the study of these proteins to assist pathologists and lab technicians in achieving a more...
A diagnosis method basing on neural network classifier, genetic algorithm (GA) and wavelet transform is proposed for a pulse width modulation voltage source inverter. It is used to detect and identify the transistor open-circuit fault. BP neural network (BPNN) is capable of recognition. However, it has shortcomings obviously. These are just advantages of GA, which has ability of global search. Thus...
It is well-known that, the pattern recognition performances assigned to RBF neural networks depends a lot by their specific training algorithms, and by the methods used for RBF center selection (e.g., a clustering technique), particularly. Having as starting point the membership of genetic algorithms to the powerful class of global optimization methods, an optimal full-genetic training procedure of...
Intrusion detection (ID) is the process of monitoring the events occurring in a computer system or network and analyzing them for signs of intrusions, defined as attempts to compromise the confidentiality, integrity, availability, or to bypass the security mechanisms of a computer or network. Internet services, and the number of Internet users increases every day this makes networks as a window for...
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