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3. Solving a new variant of the capacitated maximal covering location problem with fuzzy coverage area using metaheuristic approachesSoumen Atta, Priya Ranjan Sinha Mahapatra, Anirban Mukhopadhyay, 2022, izvirni znanstveni članek Opis: The Maximal Covering Location Problem (MCLP) is concerned with the optimal placement of a fixed number of facilities to cover the maximum number of customers. This article considers a new variant of MCLP where both the coverage radii of facilities and the distance between customer and facility are fuzzy. Moreover, the finite capacity of each facility is considered. We call this problem the capacitated MCLP with fuzzy coverage area (FCMCLP), and it is formulated as a 0–1 linear programming problem. In this article, two classical metaheuristics: particle swarm optimization, differential evolution, and two new-generation metaheuristics: artificial bee colony algorithm, firefly algorithm, are proposed for solving FCMCLP. Each of the customized metaheuristics utilizes a greedy deterministic heuristic to generate their initial populations. They also incorporate a local neighborhood search to improve their convergence rates. New instances of FCMCLP are generated from the traditional MCLP instances available in the literature, and IBM’s CPLEX solver is used to generate benchmark solutions. An experimental comparative study among the four customized metaheuristics is described in this article. The performances of the proposed metaheuristics are also compared with the benchmark solutions obtained from CPLEX. Ključne besede: Facility Location Problem (FLP), Fuzzy Capacitated Maximal Covering Location Problem (FCMCLP), Particle Swarm Optimization (PSO), Differential Evolution (DE), Artificial Bee Colony (ABC), Firefly Algorithm (FA) Objavljeno v RUNG: 08.03.2023; Ogledov: 2283; Prenosov: 0 Gradivo ima več datotek! Več... |
4. Advanced artificial intelligence system by intuitionistic fuzzy ▫$\Gamma$▫ -subring for automotive robotic manufacturingNarjes Firouzkouhi, Abbas Amini, Marziyeh Nazari, Fadi Alkhatib, Hashem Bordbar, Chun Cheng, Bijan Davvaz, Maria Rashidi, 2023, izvirni znanstveni članek Ključne besede: intelligent systems, robotic manufacturing, intuitionistic fuzzy set, image, inverse image, upper bound level, lower bound level Objavljeno v RUNG: 03.03.2023; Ogledov: 1676; Prenosov: 3 Povezava na datoteko Gradivo ima več datotek! Več... |
5. ŁUKASIEWICZ ANTI FUZZY SUBALGEBRAS OF BCK/BCI-ALGEBRASJeong Gi Kang, Hashem Bordbar, 2025, izvirni znanstveni članek Opis: Abstract. The subalgebra of BCK/BCI-algebra using Łukasiewicz anti fuzzy set
introduced by Jun is studied in this article. The concept of Łukasiewicz anti
fuzzy subalgebra of a BCK/BCI-algebra is introduced, and several properties are
investigated. The relationship between anti fuzzy subalgebra and Łukasiewicz anti
fuzzy subalgebra is given, and the characterization of a Łukasiewicz anti fuzzy subalgebra
is discussed. Conditions are found in which a Lukasiewicz anti fuzzy set is a
Lukasiewicz anti fuzzy subalgebra Finally, conditions under which ⋖-subset, Υ- subset, and anti-subset become subalgebra are explored. Ključne besede: Anti fuzzy subalgebra, Łukasiewicz anti fuzzy set, Łukasiewicz anti fuzzy subalgebra, ⋖-subset, Υ-subset, anti subset Objavljeno v RUNG: 20.02.2023; Ogledov: 1468; Prenosov: 0 Gradivo ima več datotek! Več... |
6. Dependence relations and grade fuzzy setAlessandro Linzi, Irina Elena Cristea, 2023, izvirni znanstveni članek Opis: With the aim of developing the recent theory of dependence relations, we elaborate a procedure to measure the strength of the influence of an element on another with respect to a given dependence relation on a finite set. We call this measure the degree of influence. Its definition is based on a partial hyperoperation and a directed graph which we associate with any dependence relation. We compute the degree of influence in various examples and prove some general properties. Among these properties, we find symmetries that have the potential to be applied in the realization of effective algorithms for the computations. Ključne besede: dependence relation, degree of influence, grade fuzzy set, hypercompositional structure, hyperoperation Objavljeno v RUNG: 23.01.2023; Ogledov: 2118; Prenosov: 7 Celotno besedilo (304,05 KB) Gradivo ima več datotek! Več... |
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8. BAT algorithm for improving fuzzy C-means clustering for location allocation of rural kiosks in developing countries under e-governanceRajan Gupta, Sunil K. Muttoo, Saibal K. Pal, 2016, izvirni znanstveni članek Opis: Rural Kiosks are important infrastructural pillar in rural regions for internet and basic technology facility all around the world. They are also known as Tele-centers or Common Service Centers and are majorly used by government to promote Electronic Governance. The major characteristic of setting up of Rural Kiosk is their appropriate location so that people from rural region can avail the services at minimum travel cost and time. There are lot of traditional schemes used by researchers in past for location allocation but this paper proposes the usage of Fuzzy C-Means clustering and BAT algorithm to optimize the location of Rural Kiosk. The meta-heuristic approach has produced better results as compared to normal graph theories in past. The experiment has been conducted on a random data set of 72 village
locations from India and their clusters are formed. It is found that using only Fuzzy C-Means clustering to allocate the center and by using it in combination with BAT algorithm produced
up to 25% of efficient results. This can drastically help the key stakeholders in allocation of these Rural Kiosks at right places so as to maximize their utility. Ključne besede: BAT algorithm, location allocation, rural kiosks, fuzzy C-means, e-governance, tele-centers, common service centers Objavljeno v RUNG: 01.04.2021; Ogledov: 2476; Prenosov: 0 Gradivo ima več datotek! Več... |
9. Binary division fuzzy C-means clustering and particle swarm optimization based efficient intrusion detection for e-governance systemsSunil K. Muttoo, Saibal K. Pal, 2016, izvirni znanstveni članek Opis: With the rapid rise of technology, many unusual and unwanted patterns have been observed in the communication network andrespective systems. This may be attributed to the increase of external threats that cause many security concerns. Such anomalies and unusual behavior lead to a strong need of studying and designing the Intrusion Detection Systems and Clustering. Currently,a variety of clustering methods and their combinations are used to develop an efficient intrusion detection system, but some metrics like low detection rate and high false alarm rate make these models unsatisfactory. The problem of local minima for clustering technique makes their search ability less efficient. An evolutionary technique called particle swarm optimization algorithm, that is based on swarm intelligence, shows a high global maxima search capability. In this paper, these two techniques have been combined to present a novel approach called fuzzy based particle swarm algorithm for the implementation of intrusion detection system. The experiment was conducted on a new data set called Kyoto data set with more number of anomalies. The obtained results were compared with two traditional clustering techniques based on K-Means and Fuzzy C-Means. It was observed that the proposed algorithm outperformed the other two traditional methods on the basis of the Detection Rate and False Alarm rate. In past some researchers have presented the combination of Fuzzy Based Particle Swarm Optimization algorithm to improve the intrusion detection rate,but this rate has been further improved because the algorithm performance depends on the termination condition and the fitness function value which are new in the proposed algorithm. Moreover, cluster numbers have been considered differently in the past, whereas the proposed algorithm works only on binary clustering. Ključne besede: intrusion detection, fuzzy C-means clustering, particle swarm optimization, detection rate, e-governance Objavljeno v RUNG: 01.04.2021; Ogledov: 2469; Prenosov: 0 Gradivo ima več datotek! Več... |
10. Meta-heuristic algorithms to improve fuzzy C-means and K-means clustering for location allocation of telecenters under e-governance in developing nationsRajan Gupta, Sunil K. Muttoo, Saibal K. Pal, 2019, izvirni znanstveni članek Opis: The telecenter, popularly known as the rural kiosk or common service center, is an important building block for the improvement of e-governance in developing nations as they help in better citizen engagement. Setting up of these centers at appropriate locations is a challenging task; inappropriate locations can lead to a huge loss to the government and allied stakeholders. This study proposes the use of various meta-heuristic algorithms (particle swarm optimization, bat algorithm, and ant colony optimization) for the improvement of traditional clustering approaches (K-means and fuzzy C-means) used in the facility location allocation problem and maps them for the betterment of telecenter location allocation. A dataset from the Indian region was considered for the purpose of this experiment. The performance of the algorithms when applied to traditional facility location allocation problems such as set-cover, P-median, and the P-center problem was investigated, and it was found that their efficiency improved by 20%–25% over that of existing algorithms. Ključne besede: ant colony optimization, bat algorithm, common service center, e-governance, fuzzy clustering, meta-heuristic algorithm, particle swarm optimization Objavljeno v RUNG: 01.04.2021; Ogledov: 2520; Prenosov: 11 Povezava na celotno besedilo Gradivo ima več datotek! Več... |