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Journal ArticleDOI

Integrated Ranking Algorithm for Efficient Decision Making

TL;DR: The decision making remains a prominent issue in all the problem domains and to make better decisions, multiple factors of the given problem need to be considered and evaluated.
Abstract: Decision making remains a prominent issue in all the problem domains. To make better decisions, multiple factors of the given problem need to be considered and evaluated. Multi-criteria decision-ma...
Citations
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Journal ArticleDOI
TL;DR: In recommender systems, Collaborative Filtering plays an essential role in promoting recommendation services and the conventional CF approach has limitations, namely data sparsity and cold-start problems.
Abstract: In recommender systems, Collaborative Filtering (CF) plays an essential role in promoting recommendation services. The conventional CF approach has limitations, namely data sparsity and cold-start....

10 citations

Book ChapterDOI
TL;DR: In this article , a collection of research has been carried out to identify and collect artifacts of web browsers having secrecy features for examination, validation, and find out potential ways to use the collected information during active investigations.
Abstract: Web browsers are ubiquitous applications to access public and private applications over the Internet, Intranet, and Extranet. The increased demand for cybersecurity, including data privacy, secrecy, and anonymity, becomes the reason for enhanced privacy and anonymity in common web browsers and specialized web browsers to achieve such purposes. These features are great challenges and obstacles for forensic investigators. In this paper, a collection of research will be analyzed, that have been carried out to identify and collect artifacts of web browsers having secrecy features for examination, validation, and find out potential ways to use the collected information during active investigations. As a result, live forensics can become more relevant and dependable for collecting reasonable artifacts from private browsers. From common browsers using private browsing facilities, even removing web browsers after committing criminal activities can also be identified by analyzing the registry, supporting factual evidence gathering in any Digital Forensic investigation.

8 citations

Journal ArticleDOI
01 Jun 2022-Sensors
TL;DR: An improved model in terms of precision outperforms prevailing techniques such as Multilayer Perceptron (MLP) and Linear Regression (LR) and the proposed CSRA possesses Machine-Learning (ML) techniques for ranking cloud services using parameters such as availability, security, reliability, and cost.
Abstract: Cloud Computing (CC) provides a combination of technologies that allows the user to use the most resources in the least amount of time and with the least amount of money. CC semantics play a critical role in ranking heterogeneous data by using the properties of different cloud services and then achieving the optimal cloud service. Regardless of the efforts made to enable simple access to this CC innovation, in the presence of various organizations delivering comparative services at varying cost and execution levels, it is far more difficult to identify the ideal cloud service based on the user’s requirements. In this research, we propose a Cloud-Services-Ranking Agent (CSRA) for analyzing cloud services using end-users’ feedback, including Platform as a Service (PaaS), Infrastructure as a Service (IaaS), and Software as a Service (SaaS), based on ontology mapping and selecting the optimal service. The proposed CSRA possesses Machine-Learning (ML) techniques for ranking cloud services using parameters such as availability, security, reliability, and cost. Here, the Quality of Web Service (QWS) dataset is used, which has seven major cloud services categories, ranked from 0–6, to extract the required persuasive features through Sequential Minimal Optimization Regression (SMOreg). The classification outcomes through SMOreg are capable and demonstrate a general accuracy of around 98.71% in identifying optimum cloud services through the identified parameters. The main advantage of SMOreg is that the amount of memory required for SMO is linear. The findings show that our improved model in terms of precision outperforms prevailing techniques such as Multilayer Perceptron (MLP) and Linear Regression (LR).

3 citations

Proceedings ArticleDOI
14 Jul 2022
TL;DR: A Natural Language Processing (NLP)-based decision model for the identification of the best higher education institute using MCDM methods is proposed in this paper . But, the proposed model is not suitable for the problem of selecting the best institution for higher education.
Abstract: Identification of the best institute for higher education has become one of the most challenging issues in the present education system. It has become more complicated as more institutes exist with extraordinary infrastructural facilities. Therefore, a decision model is required to identify the best institute for higher education based on multiple criteria. This article proposes a Natural Language Processing (NLP) -based decision model for the identification of the best higher education institute using MCDM methods. The existing decision models for the selection of the best higher education institutions consider a limited number of criteria for decision-making. In this proposed model, 17 criteria and 15 institute datasets have been identified for the development of the decision model through extensive research and experts opinion. The NLP-based text analysis approach is applied to extract the relevant information and convert it to a suitable format. As the relative importance of the criteria plays a crucial role in decision-making, CRITIC and Rank centroid methods are applied for the calculation of relative weights of criteria. TOPSIS method is used to generate the ranking grades of alternatives for each criterion. An objective function is defined to calculate the evaluation scores and select the best institute for higher education. It has been observed that the ranks obtained from the developed model match pretty well with the ranks obtained from other MCDM methods and the experts.

3 citations

Journal ArticleDOI
TL;DR: In this article , the authors proposed an optimal risky decision-making method based on interval type-2 fuzzy logic (IT2FL) utility functions, IT2FL entropy, and risk preference factor of online education reform.
Abstract: In the new situation of Internet plus, information technology has been widely applied in education, and hence online education has attracted wide attention from all walks of life. Today’s society is a risk society, and risk is everywhere. Online education reform is also risky, which is determined by many reasons. Some risks will cause certain losses to the online education reform, so based on risky decision-making, it is necessary to carry out online education reform under the new situation of Internet plus. At first, the risky decision-making in online education reform is analyzed, which is the risk of online education reform in risk society and the allocation logic of online education reform. Then, taking interval type-2 fuzzy logic (IT2FL) as the information environment, this study proposes the optimal risky decision-making method based on IT2FL utility functions, IT2FL entropy, and risk preference factor of online education reform to solve the multipath risky decision-making problem of online education reform. Finally, the experimental results show that, in the risky decision-making model, the decision-maker’s risk preference has an impact on the path weight and the ranking of the scheme, and the idea has a certain reference role for risky decision-making. Compared with the three benchmarks, the proposed method has the fewest ranking time with the same ranking results.

1 citations

References
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Journal ArticleDOI
TL;DR: The Grey Systeni and its applications are interdisciplinary, cutting across a variety of specialized fields, and it is evident that Grey System theory stands the test of time since 1982 as mentioned in this paper.
Abstract: Grey System theory was initiated in 1982 [7]. As far as information is concerned, the systems which lack information, such as structure message, operation mechanism and behaviour document, are referred to as Grey Systems. For example, the human body, agriculture, economy, etc., are Grey Systems. Usually, on the grounds of existing grey relations, grey elements, grey numbers (denoted by 8 ) one can identify which Grey System is, where \"grey\" means poor, incomplete, uncertain, etc. The goal of Grey Systeni and its applications is to bridge the gap existing between social science and natural science. Thus, one can say that the Grey System theory is interdisciplinary, cutting across a variety of specialized fields, and it is evident that Grey System theory stands the test of time since 1982. As the case stands, the developn~ent of the Grey System-as well as theoretical topic-is coupled with clear applications of the theory in assorted fields. The conccept of the Grey System, in its theory and successful application, is now well known in China. The application fields of the Grey System involve agriculture [23, 77-81, 911, ecology [59], economy [61, 102, 103, 1041, meteorology [58, 74,911, medicine [55, 891, history [63, 641, geography [I], industry [61, earthquake [73, 87, 881, geology [76, 1 191, hydrology [98, 1 121, irrigation strategy [261, military affairs, sports [116], traffic [67], management [30, 97, 1051, material science [82, 831, environment [ 1081, biological protection [69,70], judicial system [loo], etc. Projects which have been successfully completed with the Grey System theory and its applications are as follows: 1. Regional econonlic planning for several provinces in China; 2. To forecast yields of grain for some provinces in China:

4,126 citations

Journal ArticleDOI
TL;DR: In this article, the Promethee methods, a new class of outranking methods in multicriteria analysis, have been proposed, whose main features are simplicity, clearness and stability.

1,996 citations

Posted Content
TL;DR: The main features of the Promethee methods are simplicity, clearness and stability, a new class of outranking methods in multicriteria analysis, and some further problems are discussed.
Abstract: Abstract In this paper, we present the Promethee methods, a new class of outranking methods in multicriteria analysis. Their main features are simplicity, clearness and stability. The notion of generalized criterion is used to construct a valued outranking relation. All the parameters to be defined have an economic signification, so that the decision maker can easily fix them. Two ways of treatment are proposed: It is possible to obtain either a partial preorder ( Promethee I) or a complete one ( Promethee II), both on a finite set of feasible actions. A comparison is made with the Electre III method. The stability of the results given by the two methods is analysed. Numerical applications are given in order to illustrate the properties of the new methods and some further problems are discussed.

1,887 citations

Journal ArticleDOI
TL;DR: In this article, the authors present an ordinal regression method using linear programming to estimate the parameters of the utility function, which leads to the assessment of a set of utility functions by means of postoptimality analysis techniques in linear programming.

914 citations

Journal ArticleDOI
TL;DR: In this man-model symbiosis, phases of computation alternate with phases of decision, which allows the decision-maker to “learn” to recognize good solutions and the relative importance of the objectives.
Abstract: This paper describes a solution technique for Linear Programming problems with multiple objective functions. In this type of problem it is often necessary to replace the concept of “optimum” with that of “best compromise”. In contrast with methods dealing with a priori weighted sums of the objective functions, the method described here involves a sequential exploration of solutions. This exploration is guided to some extent by the decision maker who intervenes by means of defined responses to precise questions posed by the algorithm. Thus, in this man-model symbiosis, phases of computation alternate with phases of decision. The process allows the decision-maker to “learn” to recognize good solutions and the relative importance of the objectives. The final decision (best compromise) furnished by the man-model system is obtained after a small number of successive phases.

901 citations