Ranking Method Research Articles

Enhancing Groundwater Quality Evaluation Using Associative Rule Mining Technique with Random Forest Split Gini Indexing Algorithm for Nitrate Concentration Analysis

Human actions and changing weather patterns are contributing to the growing demand for groundwater resources. Nevertheless, evaluating the quality of groundwater is crucial. Nitrate is a significant water contaminant that can lead to blue-baby syndrome or methemoglobinemia. Therefore, it is necessary to assess the level of nitrate in groundwater. Current methods involve evaluating the quality of groundwater and integrating it into the models. The inappropriate datasets, lack of performance, and other constraints are limitations of current methods. Ground water dataset is used and pre-processed the data’s. Selected data’s are feature extracted and associated with the rule ranking. In the suggested model, the use of associative rule mining technique has been implemented to address these challenges and assess nitrate levels in groundwater. The method of rule ranking is carried out using association rule mining technique to divide the datasets. The split gini indexing algorithm is introduced in the proposed model for data classification. The Split Gini Indexing algorithm is a decision tree induction algorithm that is used to build decision trees for classification tasks. It is based on the Gini impurity measure, which measures the heterogeneity of a dataset. The quality of groundwater has been classified using Naïve Bayes, SVM, and KNN algorithms. The proposed approach's efficiency is evaluated by calculating performance metrics such as precision, accuracy, F1-score, and recall values. The suggested method in the current research attains an improved accuracy of 0.99, demonstrating enhanced performance.

A Fuzzy Optimal Base Stock System for Tolerant Clients

Base stock is an amount of stock that a company requires to maintain in order to handle an unexpected huge demand. To lerant clients are the clients who are tolerant to the company’s delayed supply, who come back to the same company even if their demands are not met within their expected time. This implies that the clients are solely relied on that company. Marketing manager requires to maintain on hand to satisfy such tolerant clients’ demands with some delay, no longer than expected by that tolerant client.This paper diagnosis the performance measures of optimal base stock system for tolerant clients in fuzzy environment. The fuzzy numbers can be modified to crisp number with the help of fuzzy ranking methods. Here the used fuzzy ranking method is prominent for de-fuzzification. The famous Triangular fuzzy number and Trapezoidal fuzzy number methods are played a major role for de-fuzzification. At last, the optimization of base stock is verified with numerical examples in fuzzy environment.

Assessing economic landscapes: city rankings (2010–2022)

Urban assessment is crucial for understanding the dynamics of city development, identifying areas for improvement, and formulating targeted policies to enhance the quality of life for residents. This study focuses on evaluating Kazakhstan’s megacities across nine indicators grouped into financial and economic condition, business development, and living standards. Using comparative analysis and ranking methods, the study assesses budgetary allocations, population dynamics, industrial growth, and the impact of strategic investments on urban development. Drawing on current economic and demographic trends, the study examines the role of cities as drivers of economic growth and highlights the importance of addressing social and economic inequalities. Through a literature review, the study contextualizes the findings within the broader discourse on urbanization and economic development, emphasizing the need for nuanced strategies to address regional disparities. Methodologically, a rating system based on quantitative indicators from 2010 to 2022 is employed, with a heatmap visualization to illustrate city rankings across various indicators. Using aggregated data on key economic indicators, the cities were classified into three categories: high-ranking, mid-ranking and low-ranking. The study contributes to a deeper understanding of urban development in Kazakhstan and provides insights for policy formulation aimed at promoting sustainable and inclusive growth across its megacities. The city ranking analysis depicts a varied economic landscape in Kazakhstani cities. High-ranked cities exhibit robust economic performance with low poverty rates, strong average salaries, and active retail trade, hinting at promising business prospects. Mid-ranked cities show mixed performances, while low-ranked cities face considerable economic challenges, including higher poverty, lower salaries, and potential declines in trade.

Multi-response Optimization of GTAW Process Parameters in Terms of Energy Efficiency and Quality

This work optimizes the current (I), voltage (V), flow rate (F), and arc gap (G) of the gas tungsten arc welding (GTAW) of the Ti40A titanium alloy to decrease the heat input (HI) and improve the ultimate tensile strength (TS) and micro-hardness (MH). The radial basis function network (RBFN) was utilized to present performance measures, while weighted principal component analysis (WPCA) and an adaptive non-dominated sorting genetic algorithm II (ANSGA-II) were applied to estimate the weights and generate optimal points. The evaluation via an area-based method of ranking (EAMR) was employed to determine the best solution. The results indicated that the optimal I, V, F, and G are 89 A, 23 V, 20 L/min, and 1.5 mm, respectively. The improvements in the TS and MH were 1.2 % and 19.8 %, respectively, while the HI was saved by 18.4 %. The RBFN models provided acceptable accuracy for prediction purposes. The ANSGA-II provides better optimality than the conventional NSGA-II. The HI, TS, and MH of the practical GTAW Ti40A could be enhanced using optimality. The optimization method could be utilized to deal with optimization problems for not only other GTAW operations but also other machining processes.

Enhancing Feature Selection in MCI Diagnosis using FDG-PET Images: Leveraging Multiple Simple Autoencoder Architectures

Alzheimer’s Disease (AD) is the most common type of neurodegenerative brain disease in elderly people. Early diagnosis of AD is crucial for providing suitable care. Positron Emission Tomography (PET) images and machine learning can be used to support this purpose. In this paper, we present a method for ranking the effectiveness of brain regions of interest (ROIs) to distinguish between stable mild cognitive impairment (sMCI) from progressive mild cognitive impairment (pMCI) in brain PET images based on AutoEncoder (AE). Experiments on the ADNI dataset show that our proposed method significantly improves classifier performance when compared to other popular feature ranking methods such as Fisher score, t-score, and LASSO. Our results suggest that instead of focusing on designing a complex AE structure, we can also use simple-but-multiple AEs for feature ranking. The proposed method could be easily applied to any image dataset where a feature selection is needed.

On a total order on the set of Z-numbers based on discrete fuzzy numbers

Z-numbers were introduced by Zadeh in 2011 as a pair of fuzzy numbers (A, B), where A is interpreted as a fuzzy restriction on the values of a variable, while B is interpreted as a measure of certainty or sureness of A. From the initial proposal, several other approaches have been introduced in order to reduce the computational cost of the involved operations. One of such approaches is called discrete Z-numbers where A and B are modelled as discrete fuzzy numbers. In this paper, the construction of total orders on the set of discrete Z-numbers is investigated for the first time. Specifically, the total order is designed for discrete Z-numbers where the second component has membership values belonging to a finite and prefixed set of values. The method relies on solid and coherent linguistic criteria and several linguistic properties are analyzed. The order involves the transformation of the first components of the discrete Z-numbers by using the credibility of the second components in the sense that a lower credibility enlarges in a greater extent the uncertainty of the first component. Then a total order on the set of discrete fuzzy numbers is applied. Finally, a practical example on how to order discrete Z-numbers is presented and a comparison with other ranking methods is performed from which the strengths of our method are stressed.

Опасность и риск: смысл и толкование терминов

The article provides an analysis of the use of «Hazard» and «Risk» terms and associated phrases in legal and regulatory-technical documents and safety practices; their possible interpretations are identified. Most often, such problems arise during the classification of productions and facilities in accordance with their level of hazard, when various documents and articles use such terms as hazard degree, risk degree, risk level, etc. When using the «Risk» term as a connotation of the «Hazard» term, the probabilistic nature of potential undesirable events is considered; at the same time, the notion «Hazard» rather refers to the sources of hazard and possible consequences of undesirable events. Possible representations of risk as a fundamentally dualistic parameter for a single indicator in order to rank hazardous facilities in accordance with their hazard degree, which caused the use of terms such as hazard degree, hazard level, hazard class, risk index, risk level, etc., have been discussed. This is achieved by using different ranking methods, risk matrices, and risk graphs. Therefore, the «Risk» notion requires additional definitions (for example, «explosion risk index»). Often, the «Risk» term in phrases means probability; however, a certain undesirable event (explosion risk, risk of injuries to personnel, risk of harm to the legitimate interests of citizens) is specified.

Measure Constraints Faced by Farm Women Using ICT Tools by Garett Ranking Method

Traditionally the extension services have focused on male farmers. In the last few decades the concern regarding farm women have been raised globally. There is immediate need to equip these farm women with relevant knowledge and skill. It is only possible if appropriate and relevant Information communication technology (ICT) tools are made available to farm women to get information related to agriculture. The present study was conducted in the Udham Singh Nagar district of Uttarakhand state to identify the constraints faced by farm women while using ICT tools. Garrett ranking was used. For this study, respondents were selected by using a Probability proportional to size (PPS) sampling method. To derive the inferences of the study, two blocks were selected for the present study. The study covered four villages & it covered 120 farm women in the selected villages. Data for the study was collected during 2019-20. Primary data was collected from farm women through personal interview method with the help of a pretested schedule. The main personal constraints noticed were lack of preference in using Information communication technology (ICT), lack of training, lack of confidence, lack of motivation and lack of time to utilize Information communication technology (ICT). The main technological constraints were language problem to use Information communication technology (ICT), complex nature of Information communication technology (ICT) restricted availability and restricted accessibility to Information communication technology (ICT) tools. The main cultural constraints were lack of faith in Information communication technology (ICT) tools, traditional belief in the existing system, discouragement from the family and society. The main infrastructural barriers were poor electricity services and poor network connectivity.

Ranking the Performances of Goalkeepers By WASPAS Method: AFC Asian Cup Qatar 2023

This study aims to evaluate and rank goalkeepers’ performances who competed in the Asian Cup Qatar 2023 according to some parameters. The sample size of the study was 22 goalkeepers. Data were obtained from the official website of the Asian Football Confederation (AFC) and Transfermarkt. Criteria used in the analysis to rank the performances of the goalkeepers were save percentage per match, number of catches and punches, and successful passes percentage per match. The criteria were weighted via the ranking method. Five steps of the WASPAS method among multi-criteria decision-making (MCDM) techniques were used to rank goalkeepers. According to the results of the analysis, GKs were ranked from 1 to 22 in terms of their performances, and the mean composite optimal value (Qi) was 0.696. The highest Qi value was 0.866, while the lowest was calculated as 0.310. According to the performance ranking, the top 3 GKs were determined as Rustam Yatimov (Tajikistan), Meshaal Barsham (Qatar), and Mathew Ryan (Australia). On the other hand, the lowest-ranked GKs were determined as Enando Ari (Indonesia), Zion Suzuki (Japan), and Rami Hamada (Palestine). Key Words: Goalkeeper, goalkeeper performance, ranking goalkeeper, WASPAS method, MCDM

ANALYSIS AND ASSESSMENT OF THE COMPETITIVE POTENTIAL OF THE TOURISM INDUSTRY ENTITIES: A METHODICAL APPROACH

The article highlights the issues of developing a methodical approach to the analysis and assessment of the competitiveness capability of tourism industry (TI) entities. The main tasks of the study include the analysis of the existing methodical approaches to the assessment of the competitive potential (CP) of business entities and the level of TI development, the justification of the author's methodical approach based on the criteria of transformation of the CP, which allows to determine the level of balance between providers of tourist services and their consumers. The author's methodical approach to the analysis and assessment of the CP of the subjects of the TI is substantiated. The main features of the methodical approaches to assessing the competitive potential of TI entities (CPTIE) are the use of quantitative assessment methods, wide coverage of indicators, an assessment of the entity's strengths and weaknesses, its competitive advantages and relevant conditions for sustainable development, extensive use of the rank method. The proposed methodical model consists of 5 blocks: Block 1 – justification of research elements; Block 2 – determination of research areas; Block 3 – selection of indicators system; Block 4 – calculation of the integral index; Block 5 – transformation of the CPTIE depending on the level of balance/imbalance between suppliers and consumers of tourism services. Each of the blocks contains structural elements of analytical research. The results of the study indicate that the proposed methodical approach to the assessment and analysis of the CPTIE can be used as a basis for developing differentiated approaches to the assessment of transformational changes depending on the phase of their current state.

Two Weighting Methods for Software-Defined Network Controllers Ranking as a Multicriteria Decision-Making Problem

Two Weighting Methods for Software-Defined Network Controllers Ranking as a Multicriteria Decision-Making Problem

Managing healthcare innovation activities in Kazakhstan for optimal effectiveness

ABSTRACT The purpose of the article is to substantiate the theoretical, methodological, and conceptual foundations for managing innovative activities in the healthcare system of the Republic of Kazakhstan and develop recommendations aimed at improving its effectiveness in modern conditions. This study employs a mixed-method approach, integrating retrospective analysis, statistical evaluation, and economic analysis to examine trends and performance in healthcare innovation within Kazakhstan. It utilizes dynamic and structural analysis to assess innovation effectiveness and identifies key factors influencing innovative activity through equity participation and ranking methods, underpinning recommendations for improved management practices. This article critically concludes that healthcare innovation in Kazakhstan must address the low effectiveness of current innovative activities, hindered primarily by insufficient demand and funding constraints. The study underscores the essential role of a robust management mechanism focused on resource allocation, service delivery efficiency, and digital technology integration. It highlights the necessity for strategic funding distribution, enhanced international cooperation, and leveraging higher education institutions for innovation drive. The findings advocate for comprehensive strategies to boost innovation’s commercial efficiency and suggest further research on implementing these strategies in the context of Kazakhstan’s unique socioeconomic landscape and healthcare needs. Priority recommendations aimed at improving the efficiency of managing the country’s healthcare innovation activities have been formed. The results obtained in the study can be useful both to the scientific community and to managers at various levels in the healthcare sector.

Self-confidence and consensus-based group decision making methods and applications

As the field of intelligent decision making continues to evolve, research on multi-attribute group decision making (MAGDM) is advancing at a steady pace. Nevertheless, existing research seldom addresses the aggregated solution of self-confidence and consensus in decision making information with diverse possibilities, despite its relevance to uncertain decision making environments. Consequently, this paper presents an approach to self-confidence and consensus-based group decision making. Firstly, the method provides a way for transforming three-parameter interval grey numbers into randomized decision making information. This establishes the foundation for the computation of possibility decision making information for uncertain decisions. Then, a method based on self-confidence and consensus is developed to determine the decision makers (DMs) weights, which is derived from the randomized decision making information. Next, a novel self-confidence index (SCI) for computing self-confidence and a new group consensus index (GCI) for computing consensus are demonstrated, and a reliability index (REI) method for randomized decision making information is given, which is used to identify high self-confidence and high consensus decision making information to improve the quality of decisions. Subsequently, a possibility ranking method is constructed based on pairwise comparisons of alternatives, taking into account density preferences, in order to obtain final possibility ranking conclusions. Finally, an illustrative example is provided to illustrate the concrete implementation process of the methods employed in this research. The efficacy of the proposed method is also demonstrated through a comparative analysis with the other methods.

Hybrid Model for Conducting Multiple Citation Analysis Operations Using the Same Citation Data

This study proposes a hybrid model, which can be used for conducting various citation analysis operations over a set of research works/papers interconnected with each other through their citations and references. Citation analysis of papers becomes important while evaluating their role and influence in a particular field and understanding their relation and connectivity of content with other important documents in the same field. The citation analysis methods can further be used for tracing the relationship between domains, keywords, and many other relative factors, based on the criteria considered for citation analysis operation. The research in the field of citation analysis, traditionally focussed on developing new citation analysis methods for better evaluation or ranking of the papers. This paper proposes a model, where multiple existing citation analysis operations can be implemented in a single platform. The proposed model calculates the result for co-citation analysis, bibliographic coupling, and citation density analysis. The process involved in the development of this model is discussed in detail in the later part of the manuscript. The process is based on computational coding, and hence special attention needs to be paid to the proper arrangement of papers in tabular form, based on the information of their year of publication and their citation network data. An algorithm for the model has been proposed in the later part of the manuscript that is based on the code formulated to find the relative data for conducting the operations.

Soil ecological risk assessment of ten industrial areas in China based on the TRIAD and VIKOR methods

The TRIAD approach is widely used as a scientific methodology available to deal with site-specific contamination scenarios. In this study, a soil environmental risk assessments (SERA) of ten industrial sites in China was conducted by ranking risks across multiple sites based on the TRIAD method, and attempted to provide an alternative method for risk ranking, the VIKOR method, when reference screening values for assessing individual indicators are unavailable. The VIKOR method was developed to address ranking and selection problems in multi-criteria decision-making, particularly in complex decision environments. The present assessments analyzed 33 chemical analysis indicators, 14 ecotoxicological indicators, and 5 ecological indicators related to soil microbial diversity, subsequently compared and discuss the differences in risk ranking results obtained using the two methods. The results of the TRIAD approach showed that six sites (including F, G, E, B, J and I) were ranked high in the risk order, which were in the moderate-risk range (Integrated risk value, 0.5–0.75). While the results of the VIKOR method showed that four sites (including F, G, H, and E) were ranked high in the risk order, followed by another four sites (including D, A, B, and C). Although there were differences in the assessment results, both methods consistently identified three sites (including F, G, and E) with relatively higher risks. The results indicated that when the TRIAD method is not applicable in special cases, the VIKOR comprehensive evaluation can be used to infer the relative ecological risk of the assessed site.

Investigation of reciprocal rank method for automatic generation control in two-area interconnected power system

In this article, the design and performance analysis of Jaya-assisted reciprocal rank-based proportional–integral–derivative controller with derivative filter (PIDn) is proposed for the automatic generation control (AGC) problem of two-area interconnected power systems. The filter with a derivative gain is used to nullify the impact of noise in the input signal. The integral of time multiplied square error (ITSE) of frequency deviations, tie-line power deviations, and area-control errors is the foundation of the goal function developed for tuning controller parameters (ACEs). A single overall objective function is created by combining these sub-objectives. ITSEs of two areas, ITSEs of tie-line power deviation, and ITSEs of ACEs of two areas are weighted and summarized to form the overall goal function. Each sub-relative goal’s importance in the control design is evaluated using the weights in the overall objective function. The weights in this article are determined using the reciprocal rank approach in a methodical manner, in contrast to earlier techniques where weights were either assumed equally by ignoring the relative relevance of sub-objectives or chosen at random. The resultant total objective function is minimized using the Jaya method. Six different test cases involving various load disturbances in the interconnected areas are used to evaluate the performance of the suggested Jaya optimizer-assisted reciprocal rank technique-based controller. Additionally, the performance of various controllers tuned with the sine cosine algorithm (SCA), salp swarm algorithm (SSA), symbiotic organisms search (SOS), Nelder–Mead simplex (NMS), and Luus–Jaakkola (LJ) algorithms is compared with that of the Jaya-tuned controller. The time domain specifications are provided for each of the six test scenarios. To display the differences in frequencies and tie-line power, the results are also shown. Statistical analysis is also provided to assess the suggested controller’s overall efficacy.

Assessment of select direct and indirect pozzolanic reactivity test outcomes with robust regression and ranking analysis

The use of pozzolanic materials as a sustainable partial replacement option for portland cement in concrete has been extensively studied over the last few decades. This study aimed to assess the pozzolanic reactivity of seven different powdered materials: pottery cull, brick powder, lightweight aggregate fines, class C fly ash, silica fume, glass powder, and dolostone. Pozzolanic reactivity was evaluated using seven different direct and indirect methods, including the Frattini test, strength activity index (SAI), ultrasound pulse velocity index (UPVI), thermogravimetric and differential thermal analyses (TG/DTA), calorimetry, electrical conductivity, and pH. Robust correlations and a ranking analysis were performed to evaluate the relationship and efficiency between various direct and indirect test methods. Results of the robust regression analyses showed that Frattini and TGA, SAI and electrical conductivity, SAI and calorimetry, and UPVI and calorimetry were well correlated, suggesting that these methods may be suitable alternatives to each other. According to the ranking method, electrical conductivity and calorimetry are the most rapid and efficient methods for the assessment of different pozzolans in comparison to other longer-duration test methods examined in this study.

Selection of unmanned aerial vehicle systems for border monitoring using the MPSI-SPOTIS method

PurposeThe present paper assesses the decision problem of selecting Unmanned Aerial Vehicle Systems (SARP) by the hybrid MPSI-SPOTIS approach for deployment in border control and transborder illicit combat.Design/methodology/approachBy the hybrid MCDA MPSI-SPOTIS approach, and from the database available in Gettinger (2019), models were filtered by Endurance, Range, Maximum Take-Off Weight (MTOW), and Payload, fitting within the classification of Categories EB 0 and 2. Category EB 1 was not considered in this study due to the limited number of models in the data source.FindingsThe use of the Multi-Criteria Decision Analysis (MCDA) tool MPSI-SPOTIS allowed the determination of weights by stochastic criteria, applied in a ranking method resistant to reverse ordering. The application of the method identified the Raybird-3 (Cat EB 0) and Searcher (Mk3) (Cat EB 2) models as the best alternatives. From a proposed clustering, other selection possibilities with close performance in the evaluation were presented. The cost criterion was not taken into consideration due to the absence of information in the data source employed. Future studies are suggested to include criteria related to the life cycle and acquisition cost of the models.Research limitations/implicationsThe cost criterion was not taken into consideration due to the absence of information in the data source used. Future studies are suggested to include criteria related to the life cycle and acquisition cost of the models.Originality/valueThis paper aims to propose a technology selection method applied to complex defense acquisitions when multiple factors influence the decision makers and it is hard to obtain a major optimum solution in multitask and multi-mission platform.

Assessment of Cybersecurity in Industry 4.0 using Delphi-Based Factor Relationships and Comprehensive Distance-Based Ranking Methods under Uncertainty

Industry 4.0 is a new revolution in which internet connection technologies are interfaced with various components of industrial systems to create the smart factories and manufacturing organizations of the future to achieve a sustainable manufacturing framework. A large number of networked devices presents a significant chance to gather important data for improving the technology of decision-making to enhance product life-cycle management. Industry 4.0 technologies will face significant challenges and obstacles due to the cybersecurity and data privacy problems suffered by current Internet technology. In actuality, cybersecurity poses an important challenge to the advancement of sustainable manufacturing. Cybersecurity architectures are widely employed to prevent intrusions and attacks on computers and networks. As a result, there is a major decrease in the adoption of Industry 4.0 technologies and the sustainable manufacturing framework within organizations. To achieve the implementation of this sustainable manufacturing in companies we suggested five cybersecurity measures and six criteria. The proposed decision-making method aims to rank the cybersecurity procedures. The ranking of these measures used a combination of Delphi-FARE (factor relationship) and COBRA (comprehensive distance-based ranking) methods based on a neutrosophic environment. The result showed that alternative one “Data Encryptions” is the best one, and alternative five “Cloud Servers” is the worst one. We conducted a sensitivity and comparison analysis to verify the stability of the model and its performance with other models and demonstrated impressive results.

An Experimental Analysis of Taguchi-Based Gray Relational Analysis, Weighted Gray Relational Analysis, and Data Envelopment Analysis Ranking Method Multi-Criteria Decision-Making Approaches to Multiple-Quality Characteristic Optimization in the CNC Drilling Process

An Experimental Analysis of Taguchi-Based Gray Relational Analysis, Weighted Gray Relational Analysis, and Data Envelopment Analysis Ranking Method Multi-Criteria Decision-Making Approaches to Multiple-Quality Characteristic Optimization in the CNC Drilling Process