• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.3
• /
• pp.755-778
• /
• 2024

In recent years, the number of devices being connected to the internet has grown enormously, as has the intrusive behavior in the network. Thus, it is important for intrusion detection systems to report all intrusive behavior. Using deep learning and machine learning algorithms, intrusion detection systems are able to perform well in identifying attacks. However, the concern with these deep learning algorithms is their inability to identify a suitable network based on traffic volume, which requires manual changing of hyperparameters, which consumes a lot of time and effort. So, to address this, this paper offers a solution using the extended compact genetic algorithm for the automatic tuning of the hyperparameters. The novelty in this work comes in the form of modeling the problem of identifying attacks as a multi-objective optimization problem and the usage of linkage learning for solving the optimization problem. The solution is obtained using the feature map-based Convolutional Neural Network that gets encoded into genes, and using the extended compact genetic algorithm the model is optimized for the detection accuracy and latency. The CIC-IDS-2017 and 2018 datasets are used to verify the hypothesis, and the most recent analysis yielded a substantial F1 score of 99.23%. Response time, CPU, and memory consumption evaluations are done to demonstrate the suitability of this model in a fog environment.

• International Journal of Computer Science & Network Security
• /
• v.24 no.1
• /
• pp.31-44
• /
• 2024

People have been using more energy in the last years. Several research studies were conducted to develop sustainable energy sources that can produce clean energy to fulfill our energy requirements. Using renewable energy sources helps to decrease the harm to the environment caused by conventional power plants. Choosing the right location and capacity for DG-RESs can greatly impact the performance of Radial Distribution Systems. It is beneficial to have a good and stable electrical power supply with low energy waste and high effectiveness because it improves the performance and reliability of the system. This research investigates the ideal location and size for solar and wind power systems, which are popular methods for producing clean electricity. A new artificial intelligent algorithm called Nutcracker Optimization Algorithm (NOA) is used to find the best solution in two common electrical systems named IEEE 33 and 69 bus systems to examine the improvement in the efficiency & reliability of power system network by reducing power losses, making voltage deviation smaller, and improving voltage stability. Finally, the NOA method is compared with another method called PSO and developed Hybrid Algorithm (NOA+PSO) to validate the proposed algorithm effectiveness and enhancement of both efficiency and reliability aspects.

• Journal of Software Engineering Society
• /
• v.26 no.1
• /
• pp.1-16
• /
• 2013

Variable length information message is a communication protocol standard in order for computer network systems to provide efficient delivery of information. The variable length information messages were developed for varying and controlling details of information in accordance with message receiver's required information level or information access level. In the previous studies, data compressing techniques have been in use for information message optimization technologies in order to reduce physical sizes of information messages. In optimization technologies for information messages, accuracy of information is considered as the most important factor; therefore, only non-loss compression techniques are applied to the optimization technologies. However, the non-loss compression based information message optimization methods are not efficient in data compression, and these are limited to efficient delivery of information in wireless network environments that have constraint bandwidth. In this paper, we attempt to optimize information in the variable length information messages at message fields in order to reduce physical sizes of messages more efficiently. To demonstrate the efficiency of our approach, we conduct optimization experiments for variable length information messages.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.20 no.6
• /
• pp.33-43
• /
• 2021

A60 class bulkhead penetration piece is a fire resistance system installed on a bulkhead compartment to protect lives and to prevent flame diffusion in a fire accident on a ship and offshore plant. This study focuses on the approximate optimization of the fire resistance design of the A60 class bulkhead penetration piece using a multi-island genetic algorithm. Transient heat transfer analysis was performed to evaluate the fire resistance design of the A60 class bulkhead penetration piece. For approximate optimization, the bulkhead penetration piece length, diameter, material type, and insulation density were considered discrete design variables; moreover, temperature, cost, and productivity were considered constraint functions. The approximate optimum design problem based on the meta-model was formulated by determining the discrete design variables by minimizing the weight of the A60 class bulkhead penetration piece subject to the constraint functions. The meta-models used for the approximate optimization were the Kriging model, response surface method, and radial basis function-based neural network. The results from the approximate optimization were compared to the actual results of the analysis to determine approximate accuracy. We conclude that the radial basis function-based neural network among the meta-models used in the approximate optimization generates the most accurate optimum design results for the fire resistance design of the A60 class bulkhead penetration piece.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.26 no.3
• /
• pp.65-77
• /
• 2001

Survivability of a network is one of the most important issues in designing present-day communication networks. the k-edge survivability of a given network is defined as the percentage of total traffic surviving the worst case failure of k edges. Although several researches calculated k-edge survivability on small networks by enumeration, prior research has considered how to calculate k-edge survivability on large networks. In this paper, we develop an efficient procedure to obtain lower and upper bounds on the k-edge survivability of a network.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.143-146
• /
• 1996

In this paper, we propose a hopfield model for solving the part-matching which is the number of parts and positions are changed. The goal of this paper is to minimize part-connection in pairs and net total path of part-connection. Therefore, this kind of problem is referred to as a combinatorial optimization problem. First of all, we review the theoretical basis for hopfield model to optimization and present two method of part-matching; Traveling Salesman Problem (TSP) and Weighted Matching Problem (WMP). Finally, we show demonstration through computer simulation and analyzes the stability and feasibility of the generated solutions for the proposed connection methods.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.38 no.8
• /
• pp.585-592
• /
• 1989

This paper presents an efficient algorithm for the reactive planning of transmission network under normal operating conditions. The optimal operation of a power system is a prerequisite to obtain the optimal investment planning. The operation problem is decomposed into a P-optimization module and a Q-optimization module, but both modules use the same objective function of generation cost. In the investment problem, a new variable decomposition technique is adopted which can operate the operation and the investment variables. The optimization problem is solved by using the gradient projection method (GPM).

• Journal of the Korean Operations Research and Management Science Society
• /
• v.11 no.2
• /
• pp.88-100
• /
• 1986

The focus of this paper is to develop the optimization procedures and analyze the complexities of the nonserial diverging branch systems in Dynamic Programming. The optimization procedure of the system is developed such that it helps to reduce the computational demands of the system. The complexity of the network is analyzed with the increasing number of nodes, branches and their connectedness to the main serial system. Determination of the optimal set of nodes for the main serial chain is also investigated.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
• /
• 1994.11a
• /
• pp.146-149
• /
• 1994

A nonlinear dynamic optimization has been performed for reactor power control system of CANDU 6 nuclear power plant considering xenon, fuel and moderator temperature feedback effects. Integral-of-Time-multiplied Absolute-Error (ITAE) criterion has been used as a performance index of the system behavior. Optimum controller gain are found by searching algorithm of Sequential Quadratic Programming (SQP). System models are referenced from most recent literatures. Signal flow network construction and optimization have been done by using commercial computer software package.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.503-506
• /
• 2005

In this study, optimization design technique for control of solid-fluid coupled force (sloshing) using evolutionary method is suggested. Artificial neural networks(ANN) and genetic algorithm(GA) is employed as evolutionary optimization method. The ANN is used to analysis of the sloshing and the genetic algorithm is adopted as an optimization algorithm. In the creation of ANN learning data, the design of experiments is adopted to higher performance of the ANN learning using minimum learning data and ALE(Arbitrary Lagrangian Eulerian) numerical method is used to obtain the sloshing analysis results. The proposed optimization technique is applied to the minimization of sloshing of the water in the tank lorry with baffles under 2 second lane change.