Biblio
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2020. Particle Swarm Optimization Algorithm with Variety Inertia Weights to Solve Unequal Area Facility Layout Problem. 2020 Chinese Control And Decision Conference (CCDC). :4240–4245.
The unequal area facility layout problem (UA-FLP) is to place some objects in a specified space according to certain requirements, which is a NP-hard problem in mathematics because of the complexity of its solution, the combination explosion and the complexity of engineering system. Particle swarm optimization (PSO) algorithm is a kind of swarm intelligence algorithm by simulating the predatory behavior of birds. Aiming at the minimization of material handling cost and the maximization of workshop area utilization, the optimization mathematical model of UA-FLPP is established, and it is solved by the particle swarm optimization (PSO) algorithm which simulates the design of birds' predation behavior. The improved PSO algorithm is constructed by using nonlinear inertia weight, dynamic inertia weight and other methods to solve static unequal area facility layout problem. The effectiveness of the proposed method is verified by simulation experiments.
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2018. Hybrid Approach to Detect Network Based Intrusion. 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA). :1–5.
In internet based communication, various types of attacks have been evolved. Hence, attacker easily breaches the securities. Traditional intrusion detection techniques to observe these attacks have failed and thus hefty systems are required to remove these attacks before they expose entire network. With the ability of artificial intelligence systems to adapt high computational speed, boost fault tolerance, and error resilience against noisy information, a hybrid particle swarm optimization(PSO) fuzzy rule based inference engine has been designed in this paper. The fuzzy logic based on degree of truth while the PSO algorithm based on population stochastic technique helps in learning from the scenario, thus their combination will increase the toughness of intrusion detection system. The proposed network intrusion detection system will be able to classify normal as well as anomalism behaviour in the network. DARPA-KDD99 dataset examined on this system to address the behaviour of each connection on network and compared with existing system. This approach improves the result on the basis of precision, recall and F1-score.