FUCOM-MARCOS based Group Decision-making using Dombi Power Aggregation of Dual Probabilistic Linguistic Information

The dual probabilistic linguistic (DPL) term sets are considered superior to probabilistic linguistic term sets. The power average operator can lessen the effects of the extreme assessing data from some decision-makers with prejudice. Further, the Dombi operators are quite flexible with the general parameter during the aggregation process. Moreover, based on deviation from the maximum consistency by the exclusion of the concern of the redundancy of the comparisons made in criteria pairs, FUCOM (full consistency method) is utilized as a subjective criteria weight computing model. Besides, MARCOS (Measurements alternatives and ranking according to compromise solution) method is based on the determination of utility degrees according to the distance from anti-ideal and ideal solutions and their aggregations. In this study, we combine the merits of power average operator, Dombi operator, FUCOM technique and MARCOS for dealing with multi-criteria group decision-making (MCGDM) problems under a DPL setting where rank of the alternatives are obtained through MARCOS method. For aggregating decision-experts preferences, we propose two types of operators, namely- DPL Dombi power weighted averaging and DPL Dombi power weighted geometric aggregation operators. We discuss the elegant properties of these proposed aggregation operators. We provide a case study regarding open source software learning management system selection to focus the practicability and usefulness of the proposed approach. Furthermore, we perform a sensitivity assessment on diverse criteria weight sets in order to test the stability of our developed intriguing approach. To this effect, we also provide a comparison between our approach with various extant methods.

Behavioral risky hesitant fuzzy linguistic multiple attribute decision making with priority degree method

In this paper, we propose a behavioral risky hesitant fuzzy linguistic multiple attribute decision making with priority degree method. First, we define a new ranking method for hesitant fuzzy linguistic term sets to compare the hesitant fuzzy linguistic evaluation information and the expectation. Second, we give a relative distance for the hesitant fuzzy linguistic term set to get the distance between the hesitant fuzzy linguistic evaluation information and expectation. Third, we use the prospect theory, the new defined ranking method and the new defined distance formula to get interval individual prospect value. Forth, we apply the average operator to get interval comprehensive prospect value. Fifth, we define a priority degree method of interval number to rank interval comprehension prospect value. Based on the above steps, we give the solution of risky hesitant fuzzy linguistic multiple attribute decision making problem. Further, we use the example to illustrate the feasibility and rationality of this behavior method and the comparative analysis between the existing decision making method for the hesitant fuzzy linguistic term.

A Hybrid Method for Complex Pythagorean Fuzzy Decision Making

This article takes advantage of advancements in two different fields in order to produce a novel decision-making framework. First, we contribute to the theory of aggregation operators, which are mappings that combine large amounts of data into more advantageous forms. They are extensively used in different settings from classical to fuzzy set theory alike. Secondly, we expand the literature on complex Pythagorean fuzzy model, which has an edge over other models due to its ability to handle uncertain data of periodic nature. We propose some aggregation operators for complex Pythagorean fuzzy numbers that depend on the Hamacher t-norm and t-conorm, namely, the complex Pythagorean fuzzy Hamacher weighted average operator, the complex Pythagorean fuzzy Hamacher ordered weighted average operator, and the complex Pythagorean fuzzy Hamacher hybrid average operator. We explore some properties of these operators inclusive of idempotency, monotonicity, and boundedness. Then, the operators are applied to multicriteria decision-making problems under the complex Pythagorean fuzzy environment. Furthermore, we present an algorithm along with a flow chart, and we demonstrate their applicability with the assistance of two numerical examples (selection of most favorable country for immigrants and selection of the best programming language). We investigate the adequacy of this algorithm by conducting a comparative study with the case of complex intuitionistic fuzzy aggregation operators.

Spectrum analysis of moving average operator and construction of time-frequency hybrid sequence operator

PurposeThe purpose of this paper is to analyze the spectral characteristics of moving average operator and to propose a novel time-frequency hybrid sequence operator.Design/methodology/approachFirstly, the complex data is converted into frequency domain data by Fourier transform. An appropriate frequency domain operator is constructed to eliminate the impact of disturbance. Then, the inverse Fourier transform transforms the frequency domain data in which the disturbance is removed, into time domain data. Finally, an appropriate moving average operator of N items is selected based on spectral characteristics to eliminate the influence of periodic factors and noise.FindingsThrough the spectrum analysis of the real-time data sensed and recorded by microwave sensors, the spectral characteristics and the ranges of information, noise and shock disturbance factors in the data can be clarified.Practical implicationsThe real-time data analysis results for a drug component monitoring show that the hybrid sequence operator has a good effect on suppressing disturbances, periodic factors and noise implied in the data.Originality/valueFirstly, the spectral analysis of moving average operator and the novel time-frequency hybrid sequence operator were presented in this paper. For complex data, the ideal effect is difficult to achieve by applying the frequency domain operator or time domain operator alone. The more satisfactory results can be obtained by time-frequency hybrid sequence operator.

Evaluation of Effect of Handle Vibration Diesel-Fueled Single-Axle Tractor on Handgrip Strength of Operators

Background: The transmission of vibration from a single-axis tractor to the human body is determined by its dynamic response; this, in turn, depends on the physical characteristics of a person's hand, the contact area, the strength of the grip, the push force of the tractor, and the position. The purpose of this work was to measure and evaluate handgrip strength and fatigue resistance for operators of a 15 horsepower single-axle tractor before and after vibration exposure. Methods: Grip strength of dominant and non-dominant hands before and after 30 minutes of tilling operations was measured and recorded. The operators performed tilling tasks with the tractor in third gear, while the vibration levels were measured at the tractor handle along with the vertical, forward, and transverse directions. Results: The average operator grip strength was 33.6 ± 2.7 and 26.3 ± 3.3 kg and the average overall grip strength declined from 39.7 to 29.31 kg, although the average fatigue strength was 27.6 and 26.5 seconds for the dominant hand before and after vibration exposure. For the non-dominant hand, the mean grip strength measured was 28.7±2.9 and 23.1±1.9 kg and the maximum grip strength was 32.79 and 26.25, while fatigue was 29.76 and 22 seconds before and after tilling respectively.Conclusion: The average reduction in grip strength suggest considerable differences in grip strength for dominant and non-dominant hands of single axle tractor operators and shows that vibration transmitted from the single axle tractor handle has a major effect on the operators.

Decision Method of Probabilistic Hesitant Fuzzy Information Based on Hamacher Aggregation Operators and MULTIMOORA

Aiming at solving the problem of probability hesitation fuzzy multi-attribute decision making, a new decision-making method of probability hesitation fuzzy multi-attribute is proposed in this paper, based on Hamacher operations and MULTIMOORA method. Firstly, probability hesitation fuzzy Hamacher operations are defined, including sum, product, scalar multiplication and exponentiation, and their properties are studied. On this basis, probability hesitation fuzzy Hamacher weighted average operator and probability hesitation fuzzy Hamacher weighted geometric average operator are proposed, and their properties are also studied. Secondly, alternative from multiple perspectives are chosen and compared by using the MULTIMOORA method. Finally, the effectiveness and feasibility of the decision-making method are verified by an example.