Aggregation operators of pythagorean fuzzy soft sets with their application for green supplier chain management

The Pythagorean fuzzy soft sets (PFSS) is a parametrized family and one of the appropriate extensions of the Pythagorean fuzzy sets (PFS). It’s also a generalization of intuitionistic fuzzy soft sets, used to accurately assess deficiencies, uncertainties, and anxiety in evaluation. The most important advantage of PFSS over existing sets is that the PFS family is considered a parametric tool. The PFSS can accommodate more uncertainty comparative to the intuitionistic fuzzy soft sets, this is the most important strategy to explain fuzzy information in the decision-making process. The main objective of the present research is to progress some operational laws along with their corresponding aggregation operators in a Pythagorean fuzzy soft environment. In this article, we introduce Pythagorean fuzzy soft weighted averaging (PFSWA) and Pythagorean fuzzy soft weighted geometric (PFSWG) operators and discuss their desirable characteristics. Also, develop a decision-making technique based on the proposed operators. Through the developed methodology, a technique for solving decision-making concerns is planned. Moreover, an application of the projected methods is presented for green supplier selection in green supply chain management (GSCM). A comparative analysis with the advantages, effectiveness, flexibility, and numerous existing studies demonstrates the effectiveness of this method.

Multi-Objective Short-Term Hydro-Thermal Scheduling Using Meta-Heuristic Approaches

Every day humans face new challenges to survive in this world. It is a big challenge to utilize hydro and thermal generating unit properly. Researchers are trying to explore new techniques to improve scheduling of generating units. Environmental matter is a big issue to modern society. This chapter suggests a well-organized and effective approach using concept of grey wolf optimization (GWO) to deal with non-linear, multi-objective, short-term, hydro-thermal scheduling (MOHTS) problem. Moreover, authors have incorporated oppositional based learning (OBL) to enhance characteristics of GWO to achieve solution more consistently and accurately. To explore authenticity of our proposed algorithms, GWO and OGWO (oppositional based GWO) are applied to multi-chain cascade of 4-hydro and 3-thermal test system. Effective constraints like valve-point loading, water discharge, water storage, etc., are considered here. Statistical comparisons with other enlisted heuristic methods are done. The projected methods solve MOHTS problem quickly and efficiently.

Detecting Outliers in High Dimensional Data Sets using Z-Score Methodology

Outlier detection is an interesting research area in machine learning. With the recently emergent tools and varied applications, the attention of outlier recognition is growing significantly. Recently, a significant number of outlier detection approaches have been observed and effectively applied in a wide range of fields, comprising medical health, credit card fraud and intrusion detection. They can be utilized for conservative data analysis. However, Outlier recognition aims to discover sequence in data that do not conform to estimated performance. In this paper, we presented a statistical approach called Z-score method for outlier recognition in high-dimensional data. Z-scores is a novel method for deciding distant data based on data positions on charts. The projected method is computationally fast and robust to outliers’ recognition. A comparative Analysis with extant methods is implemented with high dimensional datasets. Exploratory outcomes determines an enhanced accomplishment, efficiency and effectiveness of our projected methods.

Evaluation of the Innovational Development in Russia’s Arctic area

Purpose: the aim of the thesis – analyze the innovation development of the regions belonging to the Russian’s Arctic area.Methods: the methodological foundations of the research are based on modeling scenarios, analysis of open statistical sources, projected estimates and calculations, projected methods. As open statistical sources were used the data of the official statistics, analytical materials of international organizations, federal and regional authorities.Results: the result of the study is existing methods for assessing the innovative development of the regions, analyze of the innovation development among regions belonging to the Russian’s Arctic area. In addition, on the basis of the calculations carried out, the advantages and obvious drawbacks of the methods common today, as well as the presence of a connection between them, were identified.Conclusions and Relevance: the calculations, which allow to evaluate the innovative development, showed that in the regions of the circumpolar zone there is a low level of innovative development, which in turn becomes an obstacle to the implementation of large investment projects for the development of new fields. In such conditions, it is necessary to create research and development sites, however, since there are no prerequisites, not in the territory of the Arctic zone, but adjacent regions, where prerequisites for scientific research have already been created.

Regarding Rational Exponential and Hyperbolic Functions Solutions of Conformable Time-Fractional Phi-four Equation

In this study, we actually want to explore the time-fractional Phi-four equation via two methods, the exp a function method and the hyperbolic function method. We transform a fractional order dierential equation into an ordinary differential equation using a wave transformation and the fractional derivative in conformable form. Then, the resulting equation has successfully been explored for new explicit exact solutions. The procured solutions are simply showed the effectiveness and plainness of the projected methods.

EVALUATION OF THE REGIONAL EFFECTS FROM REALIZATION OF INVESTMENT PROJECTS IN THE CIRCUMPOLAR ZONE

Purpose: the aim of the thesis – analyze the development of the oil and gas sector of the Yamal-Nenets Autonomous District and assess the influence exerted by them on the socio-economic and environmental dynamics of the region.Methods:the methodological foundations of the research are based on modeling scenarios, analysis of open statistical sources, projected estimates and calculations, projected methods. As open statistical sources were used the data of the official statistics, analytical materials of international organizations, federal and regional authorities.Results:the main result of the research is the author's methodology for assessing regional effects arising from the implementation of investment projects. Based on the created methodology, regional effects resulting from the implementation of investment projects in the Yamal-Nenets Autonomous District were identified, according to the analysis of which developed recommendations to strengthen their localization in the region.Conclusions and Relevance:during the analyzed period the carried out calculations of regional effects showed that the positive direct effects emerge in the economic sector only while indirect ones are too weak in the Yamal-Nenets Autonomous District. In these conditions, the regional authorities face the problem to strengthen the localization of direct and indirect effects in the region, because the investment projects can be a locomotive for the development of the region’s prosperity.

Q- ABSORPTION RA TIO AND SIMULTANEOUS EQ UATION SPECTROPHOTOMETRIC METHODS FOR SIMULTANEOUS ESTIMATION OF FENBENDAZOLE AND NICLOSAMIDE IN PURE DRUG AND PHARMACEUTICAL FORMULATIONS

Two simple, accurate, sensitive and economical spectrophotometric methods have been developed and subsequently validated for determination of fenbendazole (FEN) and niclosamide (NIC) in bulk and pharmaceutical formulation. For the simultaneous equation method, the estimation of FEN and NIC was carried out at 227nm (λmax of FEN) and 332nm (λmax of NIC), respectively. For Q - absorption ratio method, estimation of FEN was carried out at 227nm (λmax of FEN) and of NIC at 306 nm (isobestic point of both drugs). Calibration curves of FEN and NIC were found to be linear in the concentration ranges of 3-9 ?g/mL and 10-30 ?g/mL, respectively, with their correlation coefficient values (r2 ) being more than 0.995. In the precision study, the % RSD value was found within limits (RSD < 2%). The percentage recovery at various concentration levels varied from 99.81 to 100 % for FEN and 99.86 to 100 % for NIC confirming that the projected methods are termed as an accurate and it can be applied successfully for the simultaneous estimation of FEN and NIC in pure and pharmaceutical dosage form.