A Self-Tuned Simulated Annealing Algorithm Using Hidden Markov Model

Limam, Mohamed; Afia, Abdellatif El; Chiheb, Raddouane

doi:10.11591/ijece.v8i1.pp291-298

Cited by 14 publications

(6 citation statements)

References 24 publications

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“…Supervised learning algorithm is applied to a dataset that has features and each of those features associated with a label. However, deep learning algorithms comes under unsupervised learning algorithms which are applied to a dataset which has many features in order to learn useful properties from the structure of the dataset [20].…”

Section: Deep Learning Models For Intrusion Detection System In Manetmentioning

confidence: 99%

A technical review and comparative analysis of machine learning techniques for intrusion detection systems in MANET

Laqtib

Yassini

Hasnaoui

2020

IJECE

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Machine learning techniques are being widely used to develop an intrusion detection system (IDS) for detecting and classifying cyber attacks at the network-level and the host-level in a timely and automatic manner. However, Traditional Intrusion Detection Systems (IDS), based on traditional machine learning methods, lacks reliability and accuracy. Instead of the traditional machine learning used in previous researches, we think deep learning has the potential to perform better in extracting features of massive data considering the massive cyber traffic in real life. Generally Mobile Ad Hoc Networks have given the low physical security for mobile devices, because of the properties such as node mobility, lack of centralized management and limited bandwidth. To tackle these security issues, traditional cryptography schemes can-not completely safeguard MANETs in terms of novel threats and vulnerabilities, thus by applying Deep learning methods techniques in IDS are capable of adapting the dynamic environments of MANETs and enables the system to make decisions on intrusion while continuing to learn about their mobile environment. An IDS in MANET is a sensoring mechanism that monitors nodes and network activities in order to detect malicious actions and malicious attempt performed by Intruders. Recently, multiple deep learning approaches have been proposed to enhance the performance of intrusion detection system. In this paper, we made a systematic comparison of three models, Inceprtion architecture convolutional neural network Inception-CNN, Bidirectional long short-term memory (BLSTM) and deep belief network (DBN) on the deep learning-based intrusion detection systems, using the NSL-KDD dataset containing information about intrusion and regular network connections, the goal is to provide basic guidance on the choice of deep learning methods in MANET.

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Section: Deep Learning Models For Intrusion Detection System In Manetmentioning

confidence: 99%

A technical review and comparative analysis of machine learning techniques for intrusion detection systems in MANET

Laqtib

Yassini

Hasnaoui

2020

IJECE

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“…Then, the temperature is lowered slowly to avoid cracking to minimize the energy used [26]. SA's flow can helps GA's individual to get convergence to a minimum global [27]. The higher the temperature and the lower the value of the solution, the greater the chance of receiving a less than optimal solution [28].…”

Section: Simulated Annealingmentioning

confidence: 99%

“…In this study, SA will generate neihborhood solution by using Scramble Mutation [27]. At this operator two randomly selected points are selected and switch the chromosome position between two points randomly for example show in…”

Section: Neighborhood Searchmentioning

confidence: 99%

Hybrid Genetic Algorithms and Simulated Annealing for Multi-trip Vehicle Routing Problem with Time Windows

Ariyani¹,

Mahmudy²,

Anggodo³

2018

IJECE

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Vehicle routing problem with time windows (VRPTW) is one of NP-hard problem. Multi-trip is approach to solve the VRPTW that looking trip scheduling for gets best result. Even though there are various algorithms for the problem, there is opportunity to improve the existing algorithms in order gaining a better result. In this research, genetic algoritm is hybridized with simulated annealing algoritm to solve the problem. Genetic algoritm is employed to explore global search area and simulated annealing is employed to exploit local search area. Four combination types of genetic algorithm and simulated annealing (GA-SA) are tested to get the best solution. The computational experiment shows that GA-SA1 and GA-SA4 can produced the most optimal fitness average values with each value was 1.0888 and 1.0887. However GA-SA4 can found the best fitness chromosome faster than GA-SA1.

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“…Because of the stochastic behaviors of many computer systems, probabilistic structures are more useful for modeling such systems [4][5][6]. Markov chains and Markov decision processes (MDPs) are wellknown structures for modelling stochastic systems and are widely used in artificial intelligence, economy, operations research and software engineering [7][8][9]. Several examples of the stochastic systems and their modelling are available in [3,4,7].…”

Section: Introductionmentioning

confidence: 99%

Improving Graph-based methods for computing qualitative properties of markov decision processes

Mohagheghi

Salehi

2020

IJEECS

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<span>Probabilistic model checking is a formal verification method, which is used to guarantee the correctness of the computer systems with stochastic behaviors. Reachability probabilities are the main class of properties that are proposed in probabilistic model checking. Some graph-based pre-computation can determine those states for which the reachability probability is exactly zero or one. Iterative numerical methods are used to compute the reachability probabilities for the remaining states. In this paper, we focus on the graph-based pre-computations and propose a heuristic to improve the performance of these pre-computations. The proposed heuristic approximates the set of states that are computed in the standard pre-computation methods. The experiments show that the proposed heuristic can compute a main part of the expected states, while reduces the running time by several orders of magnitude.</span>

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A Self-Tuned Simulated Annealing Algorithm Using Hidden Markov Model

Cited by 14 publications

References 24 publications

A technical review and comparative analysis of machine learning techniques for intrusion detection systems in MANET

A technical review and comparative analysis of machine learning techniques for intrusion detection systems in MANET

Hybrid Genetic Algorithms and Simulated Annealing for Multi-trip Vehicle Routing Problem with Time Windows

Improving Graph-based methods for computing qualitative properties of markov decision processes

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