Phishing attacks are one of the most damaging attacks for internet users. Detecting these attacks is one of the main challenges in the internet security due to their lack of unpredictable nature. Machine learning tech...
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ISBN:
(数字)9798350329797
ISBN:
(纸本)9798350329803
Phishing attacks are one of the most damaging attacks for internet users. Detecting these attacks is one of the main challenges in the internet security due to their lack of unpredictable nature. Machine learning techniques are suitable methods to detect these attacks. The accuracy of these methods is highly dependent on the features of the data. This paper proposes a hybrid feature selection approach based on Bee algorithm and Logistic Regression method, which detects phishing attacks accurately by selecting an appropriate feature subset. The results show that the proposed approach has been able to increase the detection accuracy of phishing attacks by 1.23%, using a random forest algorithm, in comparison to previous works with 6.66% less features.
This paper presents a system of systems approach to implement high-speed searching to solve complex optimization problems. In most optimization techniques, parallel computation is not effective due to the complexity i...
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ISBN:
(纸本)9781424481972;9781424481965
This paper presents a system of systems approach to implement high-speed searching to solve complex optimization problems. In most optimization techniques, parallel computation is not effective due to the complexity in algorithm. Here, the search sp ace is distributed within processing power of high performance computing resources. The methodology takes advantage of the bees algorithm and adapts it for best performance in a cluster grid computing environment. The effectiveness of the approach is verified by solving the problem of efficiency in a power plant by economizing fuel cost, efficiency of transmission losses and environmental hazardous emissions.
＜正＞People have learnt from biological system behaviours and structures to design and develop a number of different kinds of optimisation algorithms that have been widely used in both theoretical study and practical...
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＜正＞People have learnt from biological system behaviours and structures to design and develop a number of different kinds of optimisation algorithms that have been widely used in both theoretical study and practical applications in engineering and business *** efficient supply chain is very important for companies to survive in global competitive ***
This research paper explores hybrid anomaly detection frameworks combining Particle Swarm Optimization (PSO), Bee algorithm (ABC), and Genetic algorithm (GA) using the CICIDS2017 dataset for Wireless Sensor Networks (...
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ISBN:
(数字)9798331532956
ISBN:
(纸本)9798331532963
This research paper explores hybrid anomaly detection frameworks combining Particle Swarm Optimization (PSO), Bee algorithm (ABC), and Genetic algorithm (GA) using the CICIDS2017 dataset for Wireless Sensor Networks (WSNs). It evaluates their effectiveness across diverse network conditions, focusing on anomaly detection accuracy, false positives, and computational efficiency. The study aims to advance anomaly detection methodologies in WSNs by contributing insights into bio-inspired algorithms' impact on anomaly detection. It targets the research community, industry professionals, and scholars, emphasizing the documentation of methodologies and suggesting future research on hybridization techniques, dynamic adaptation, edge computing integration, and machine learning fusion for enhanced anomaly detection in WSNs, fostering improved network security and adaptability.
This paper presents the optimization of the performances of a controlled zero ripple input current high boost dc-dc converter with coupled inductors. In particular, an optimization of PID and LQR controllers design is...
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ISBN:
(纸本)9781467388634
This paper presents the optimization of the performances of a controlled zero ripple input current high boost dc-dc converter with coupled inductors. In particular, an optimization of PID and LQR controllers design is presented, using three heuristic methods: Genetic, Particle Swarm and bees algorithms. A comparison between the PID and LQR controllers, with and without optimization, is presented together with the analysis of effectiveness of the three heuristic algorithms to design the control strategies.
In robot emergency rescue scenarios, it is common for communication between robots to be restricted, allowing interaction only within localized communication ranges. However, commonly proposed task allocation algorith...
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ISBN:
(数字)9798350354409
ISBN:
(纸本)9798350354416
In robot emergency rescue scenarios, it is common for communication between robots to be restricted, allowing interaction only within localized communication ranges. However, commonly proposed task allocation algorithms with weak communication models often focus on communication quality while neglecting communication distance. Consequently, this paper introduces a Bernoulli communication model incorporating distance information as the communication model. Subsequently, a two-stage distributed task allocation algorithm is proposed based on this communication model. In the convergence stage, each robot utilizes the K-means algorithm to determine the target task group and employs a distributed bee algorithm to select the target task. In the dispersion stage, robots use an improved distributed genetic algorithm to allocate remaining tasks, exchanging optimal solutions with other robots, thereby achieving conflict-free autonomous task allocation. Finally, real-time simulations are conducted to validate that this algorithm effectively resolves the multi-robot task allocation problem within the localized communication model.
This paper aims to present an experimental investigation for optimum tribological behavior (wear depth and coefficient of friction) of electroless Ni-P-Cu coatings based on four process parameters using artificial bee...
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This paper aims to present an experimental investigation for optimum tribological behavior (wear depth and coefficient of friction) of electroless Ni-P-Cu coatings based on four process parameters using artificial bee colony algorithm. Experiments are carried out by utilizing the combination of three coating process parameters, namely, nickel sulphate, sodium hypophosphite, and copper sulphate, and the fourth parameter is postdeposition heat treatment temperature. The design of experiment is based on the Taguchi L27 experimental design. After coating, measurement of wear and coefficient of friction of each heat-treated sample is done using a multitribotester apparatus with block-on-roller arrangement. Both friction and wear are found to increase with increase of source of nickel concentration and decrease with increase of source of copper concentration. Artificial bee colony algorithm is successfully employed to optimize the multiresponse objective function for both wear depth and coefficient of friction. It is found that, within the operating range, a lower value of nickel concentration, medium value of hypophosphite concentration, higher value of copper concentration, and higher value of heat treatment temperature are suitable for having minimum wear and coefficient of friction. The surface morphology, phase transformation behavior, and composition of coatings are also studied with the help of scanning electron microscopy, X-ray diffraction analysis, and energy dispersed X-ray analysis, respectively.
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