Topic
Operator (computer programming)
About: Operator (computer programming) is a research topic. Over the lifetime, 40896 publications have been published within this topic receiving 671452 citations. The topic is also known as: operator symbol & operator name.
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TL;DR: In this article, the convergence problem of Ishikawa and Mann iterative sequences for strongly pseudo-contractive mappings without the Lipschitz condition has been studied and the results presented in this paper improve and extend the corresponding results in [ 4, 5, 7, 10, 12, 15, 16 ] in the more general setting.
250 citations
TL;DR: A new method for Pythagorean fuzzy multiple-criteria decision-making (MCDM) problems with aggregation operators and distance measures with the main advantage that it uses distance measures in a unified framework between the ordered weighted averaging (OWA) operator and weighted average (WA) that considers the degree of importance of each concept in the aggregation.
Abstract: As a generalization of intuitionistic fuzzy set, the Pythagorean fuzzy set is interesting and very useful in modeling uncertain information in real-world decision-making problems. In this paper, we develop a new method for Pythagorean fuzzy multiple-criteria decision-making (MCDM) problems with aggregation operators and distance measures. First, we present the Pythagorean fuzzy ordered weighted averaging weighted average distance (PFOWAWAD) operator. The main advantage of the PFOWAWAD operator is that it uses distance measures in a unified framework between the ordered weighted averaging (OWA) operator and weighted average (WA) that considers the degree of importance of each concept in the aggregation. Some of its main properties and special cases are studied. Then, based on the proposed operator, a hybrid TOPSIS method, called PFOWAWAD-TOPSIS is introduced for Pythagorean fuzzy MCDM problem. Finally, a numerical example is provided to illustrate the practicality and feasibility of the developed method.
250 citations
TL;DR: A method based on the ET-WG and ET-OWG operators for multiple attribute group decision-making is presented and the ranking of alternative or selection of the most desirable alternative(s) is obtained by the comparison of 2-tuple linguistic information.
Abstract: With respect to multiple attribute group decision-making problems with linguistic information of attribute values and weight values, a group decision analysis is proposed. Some new aggregation operators are proposed: the extended 2-tuple weighted geometric (ET-WG) and the extended 2-tuple ordered weighted geometric (ET-OWG) operator and properties of the operators are analyzed. Then, A method based on the ET-WG and ET-OWG operators for multiple attribute group decision-making is presented. In the approach, alternative appraisal values are calculated by the aggregation of 2-tuple linguistic information. Thus, the ranking of alternative or selection of the most desirable alternative(s) is obtained by the comparison of 2-tuple linguistic information. Finally, a numerical example is used to illustrate the applicability and effectiveness of the proposed method.
249 citations
TL;DR: This paper investigates the multiple attribute decision making (MADM) problems with intuitionistic fuzzy numbers and develops some new Einstein hybrid aggregation operators, such as the intuitionism fuzzy Einstein hybrid averaging (IFEHA) operator and intuitionistic furry Einstein hybrid geometric (IFEHG) operator.
Abstract: Intuitionistic fuzzy information aggregation plays an important part in intuitionistic fuzzy set theory, which has emerged to be a new research direction receiving more and more attention in recent years. In this paper, we investigate the multiple attribute decision making (MADM) problems with intuitionistic fuzzy numbers. Then, we first introduce some operations on intuitionistic fuzzy sets, such as Einstein sum, Einstein product, and Einstein exponentiation, and further develop some new Einstein hybrid aggregation operators, such as the intuitionistic fuzzy Einstein hybrid averaging (IFEHA) operator and intuitionistic fuzzy Einstein hybrid geometric (IFEHG) operator, which extend the hybrid averaging (HA) operator and the hybrid geometric (HG) operator to accommodate the environment in which the given arguments are intuitionistic fuzzy values. Then, we apply the intuitionistic fuzzy Einstein hybrid averaging (IFEHA) operator and intuitionistic fuzzy Einstein hybrid geometric (IFEHG) operator to deal with multiple attribute decision making under intuitionistic fuzzy environments. Finally, some illustrative examples are given to verify the developed approach and to demonstrate its practicality and effectiveness.
249 citations
19 Apr 1995
TL;DR: Using higher-level languages, like VHDL, facilitates the development of custom operators without significantly impacting operator performance or area, as well as properties, including area consumption and speed of working arithmetic operator units used in real-time applications.
Abstract: Many algorithms rely on floating point arithmetic for the dynamic range of representations and require millions of calculations per second. Such computationally intensive algorithms are candidates for acceleration using custom computing machines (CCMs) being tailored for the application. Unfortunately, floating point operators require excessive area (or time) for conventional implementations. Instead, custom formats, derived for individual applications, are feasible on CCMs, and can be implemented on a fraction of a single FPGA. Using higher-level languages, like VHDL, facilitates the development of custom operators without significantly impacting operator performance or area. Properties, including area consumption and speed of working arithmetic operator units used in real-time applications, are discussed.
248 citations