Among the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On these bases, this work aims to improve FA using variable neighborhood search (VNS) as a local search method, providing VNS the benefit of the trade-off between the exploration and exploitation abilities. The proposed FA-VNS allows fireflies to improve the clustering solutions with the ability to enhance the clustering solutions and maintain the diversity of the clustering solutions during the search process using the perturbation operators of VNS. To evaluate the performance of the algorithm, eight benchmark datasets are utilized with four well-known clustering algorithms. The comparison according to the internal and external evaluation metrics indicates that the proposed FA-VNS can produce more compact clustering solutions than the well-known clustering algorithms.
With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect
... Show More<p>The polyacrylonitrile (PAN)/polysulfone (PSF) blended polymer membranes were modified by decaethylene glycol monododecyl ether (C<sub>12</sub>EO<sub>10</sub>) as a non-ionic surfactant. Polymeric solutions containing 17 wt.% of both PAN and PSF with a ratio of 80/20, and C<sub>12</sub>EO<sub>10</sub> with a mass concentration of 6 wt.% and aluminium oxide (Al<sub>2</sub>O<sub>3</sub>) nanoparticles with varying concentrations (1, 2, and 3 wt.%) were prepared. Adding 6 wt.% of C<sub>12</sub>EO<sub>10</sub> to the casting solution formed a membrane with distinguished hydrophilicity and fouling resistance, higher porosity, appreciable pe
... Show MoreA skip list data structure is really just a simulation of a binary search tree. Skip lists algorithm are simpler, faster and use less space. this data structure conceptually uses parallel sorted linked lists. Searching in a skip list is more difficult than searching in a regular sorted linked list. Because a skip list is a two dimensional data structure, it is implemented using a two dimensional network of nodes with four pointers. the implementation of the search, insert and delete operation taking a time of upto . The skip list could be modified to implement the order statistic operations of RANKand SEARCH BY RANK while maintaining the same expected time. Keywords:skip list , parallel linked list , randomized algorithm , rank.
In many scientific fields, Bayesian models are commonly used in recent research. This research presents a new Bayesian model for estimating parameters and forecasting using the Gibbs sampler algorithm. Posterior distributions are generated using the inverse gamma distribution and the multivariate normal distribution as prior distributions. The new method was used to investigate and summaries Bayesian statistics' posterior distribution. The theory and derivation of the posterior distribution are explained in detail in this paper. The proposed approach is applied to three simulation datasets of 100, 300, and 500 sample sizes. Also, the procedure was extended to the real dataset called the rock intensity dataset. The actual dataset is collecte
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Abstract
The twentieth century French novel had undergo a significant change that took the form of a radical move from the traditional son who follows his father to one who no way prevalent in the classical French novel. The new son in the 2Oth century novel finds himself emotionally attached which both became a new trend and approach in novel writing.
Marcel Proust's novel which can be considered a source of inspiration for most of 2Oth century novelists is a good example of the mother supremacy which is crystal clear from the first page through its parts and chapters till the last page. In fact, Proust had written a completely different novel from the Balzacian conventions. Unlike the latter's novels, Pro
... Show MoreThe research aims to identify the concept of green taxes and their role in reducing environmental pollution through the poll of Abnh of taxpayers and employees of the General Authority for taxes totaling 200 individual .autam adoption of the resolution as a tool head for the collection of data and information from the sample and analyzed their responses using a statistical program (spss - 10), and calculating the percentages and the arithmetic mean, standard deviation and research found to a number of conclusions, notably the lack of legislation with the challenges and the difficulty of the existence of a measure or a standard lack of planning for the application of environmental taxes that the state taxation application between the Gene
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