Multi-criteria Analysis Model Research Articles

Multi-modal and multi-criteria conflict analysis model based on deep learning and dominance-based rough sets: Application to clinical non-parallel decision problems

The non-parallel disease progression and curative effect are the difficulties of clinical diagnosis and treatment decisions. Experts (doctors) constantly summarize these non-parallel phenomena for more accurate diagnosis and treatment. In order to discover the mechanism of clinical non-parallel decision-making, this paper constructs a multi-modal and multi-criteria conflict analysis method based on deep learning (DL) and dominance-based rough sets (DRSA). First, for multi-modal attribute information, we adopted a deep learning based visual attention distribution to focus on the priority areas of images, a deep residual network is used for a feature extractor. The dominant characteristics of the attributes are considered, and the dominant similarity relationship based on cosine similarity is constructed using DRSA. Second, conditional attributes are used to classify objects and predict clinical progression (outcome). At the same time, the objects are classified according to decision attributes based on DRSA. Third, the Pawlak conflict analysis is introduced to analyze the consistency between the predicted results of conditional attributes and the practical results generated by decision attributes. Finally, four clinically non-parallel decision datasets are used, including colorectal cancer (CRC), membranous nephropathy (MN), rheumatoid arthritis (RA) diagnosis and MN efficacy evaluation, to verify the applicability and validity of the proposed model and discover the non-parallel decision mechanism of different diseases. This paper constructs a data-driven clinical decision research paradigm, and provides a research approach to a wide range of non-parallel decision-making problems.

Integrated flood hazard assessment using multi-criteria analysis and geospatial modeling

Floods are one of the most prevalent disasters worldwide, including in the capital city of Indonesia. Multi-criteria decision analysis is combined with Geographic Information Systems to produce a mapping of flood hazard areas. The weighting for each parameter is based on six criteria: rainfall, slope gradient, topography, soil type, land cover, and distance from rivers. The flood hazard map is validated using inundation data from the Regional Disaster Management Agency for the years 2015 and 2020. From the general analysis, it can be determined that the parameter most influencing floods is rainfall with a weight of 0.270, followed by slope gradient at 0.164, topography at 0.124, soil type at 0.096, land cover at 0.190, and distance from rivers at 0.155. Therefore, through mapping using QGIS, it is revealed that in 2002, highly flood hazard areas comprised 20.99% of the total Ciliwung Watershed area, which increased to 24.31% in 2020. The validation of the flood hazard map was conducted by recording the coordinate points of flood incidents in 2015 and 2020, revealing that the affected areas within the Ciliwung Watershed occurred in high to very high vulnerability zones. This research demonstrates that flood events in the study area occurred in high to very high flood hazard zones. The results of this study are considered valuable and important for providing accurate information to local governments to develop cost-effective and efficient strategies in dealing with potential flood hazards.

Assessment of machine learning algorithms and new hybrid multi-criteria analysis for flood hazard and mapping.

Floods in Iran cause a lot of damage in different places every year. The 2019 floods of the Gorgan and Atrak rivers basins in the north of Iran were one of the most destructive events in this country. Therefore, investigating the flood hazard of these areas is very necessary to manage probable future floods. For this purpose, in the present study, the capability of Random Forest (RF) and Support Vector Machine (SVM) algorithms was investigated in combination with Sentinel series and Landsat-8 images to prepare the 2019 flood map. Then, the flood hazard map of these areas was prepared using the new hybrid Fuzzy Best Worse Model-Weighted Multi-Criteria Analysis (FBWM-WMCA) model. According to the results of the FBWM-WMCA model, 38.58%, 50.18%, 11.10%, and 0.14% of the Gorgan river basin and 45.11%, 49.96%, 4.17%, and 0.076% of the Atrak river basin are in high, medium, low, and no hazards, respectively. The highest flood hazard areas in Gorgan and Atrak rivers basins in the north, northwest, west, and east, and south and southwest are mostly at medium flood hazard. Also, the results of RF and SVM algorithms with an overall accuracy of more than 85% for Sentinel-1, Sentinel-2, and Landsat-8 images and 80% for Sentinel-3 images indicate that the flooding is related to the western, southwestern, and northern regions including agricultural, bare lands and built up. According to the obtained results and the efficiency of the FBWM-WMCA model, the Gorgan and Atrak rivers basins need proper planning for flood hazard management.

Urban expansion effects on real estate ecosystems: Identification and neutrosophic analysis of causal dynamics

Real estate ecosystems are the result of symbiotic relationships between different types of real estate, including residential, commercial, or industrial properties. Maintaining a balance among these categories is essential for these ecosystems’ ability to function properly. Real estate currently is largely a product of urban expansion caused by population increases and distances from primary-sector industries. The unplanned growth of urban areas can have profound consequences for local residents’ health and the environment. However, when well structured, urbanization can have a positive effect on societies’ well-being. The relationship between this expansion and its impact on real estate ecosystems is an extremely complex, subjective topic, so decision makers cannot apply just one solution when making plans. This study develops a multicriteria analysis model to support decision making processes, which provides a structured understanding of urban expansion effects on real estate ecosystems and deals with the inherent subjectivity and complexity of this decision problem. Cognitive mapping and decision-making trial and evaluation laboratory (DEMATEL) technique were combined in a neutrosophic environment to incorporate uncertainty and produce a more realistic analysis system, thereby overcoming various limitations of previous research on urban expansion (e.g., unclear way by which relevant factors/criteria are identified in most cases, and lack of analyses dealing with the dynamics of their causal relationships). Decision makers with professional experience in relevant areas collaborated to provide essential input used to create the proposed model. External experts validated the results, confirming the potential of our analysis system for real-life applications.

A decision support software system for cryptocurrency traders on the Trading View platform

The work carried out a comparative analysis of scientific publications regarding the possibility of predicting the direction of the cryptocurrency exchange rate using the data of open numerical indicators, based on the results of which it can be concluded that due to the volatility of the cryptocurrency market and the need for accurate forecasting, there is a need to create an aggregated indicator that will take into account the current price exchange rate asset, parameters of simple indicators, trading volume, etc. In addition, this indicator will be a parameter for the application of a multi-criteria analysis model in the process of supporting decision-making for cryptocurrency trading. A software decision support system for cryptocurrency traders on the Trading View platform has also been developed, which allows the cryptocurrency trader to get the value of the current situation of the cryptocurrency market in the form of a value using the method of weighting coefficients and selected indicators. Among the selected indicators: RSI, MA, CCI, Stochastic Oscillator, OBV, ADX, CMF to determine the moment of opening a position, and Fibonacci Retracement, Ichimoku Cloud to determine the closing of positions. Taking into account all the indicators and the coefficients determined for them, the obtained range of values is from 0 % to 100 %. If the value of the indicator exceeds the threshold of 20 %, it means that it is necessary to inform the trader about a possible entry point. That is, a value of 20 % to 40 % is weak performance, 40 % to 60 % is medium performance, 60 % to 80 % is strong performance, and a value greater than 80 % will not be overlapped by new pyramiding values for a better overall indicator success rate. The value of the indicator determines the potential effectiveness of opening positions, and thanks to the RSI indicator, the direction of opening positions is determined. The direction of the position is divided into long and short. An indicator has been developed for the TradingView platform, which, unlike existing simple indicators, collects data from open access and calculates a potential point for opening a position. Obtaining the numerical value of a single indicator saves the trader time to review and analyze a collection of indicators and time to decide on opening a position, as the cryptocurrency market is known for its sudden volatility, where a decision must be made quickly.

Measuring Customer Satisfaction Using Multi-Criteria Analysis Model of Customer Satisfaction to Evaluate Product Lines

Today, customer retention and growth is the first goal. Companies have taken a heavytoll on each customer, and competitors are constantly seeking to steal them. Satisfiedcustomers have many benefits for the company, they are less sensitive to prices, will bea customer for a long period of time, and give a favorable view of the company and itsproducts and services to others. Paying attention to the factors that are less importantfrom the customer's point of view and evaluating these factors leads to spendingresources in areas that have less impact on customer behavior, so understanding thefactors that have the greatest impact on customer satisfaction to the organization tomove in this will help. In this study, we intend to use the operational data of the linesand customer satisfaction scales to evaluate the relative efficiency of product lines usingthe network data envelopment analysis method. In order to achieve this goal andquantify the data obtained from the questionnaire, another linear programming methodcalled multi-criteria satisfaction analysis will be used. Another innovation of thisresearch is the application of customer expectations in the data envelopment analysismole because most researchers that focus on quality do not consider this component intheir evaluation model. The results indicate that the distribution system is the mosteffective factor and resources and supply is the most effective factor affecting customersatisfaction.

The Italian National Strategy for Sustainable Development and the Covid-19 impact: a regional analysis

The Italian National Strategy for Sustainable Development plays an important role in the national implementation of the 17 Goals for sustainable development set globally through the 2030 Agenda of the United Nations. The achievement of such goals in Italy is linked to the strategic choices and objectives established at the national level. The purpose of this work is to monitor the performance of the 20 Italian regions in 4 of the 5 areas of the Agenda (People, Planet, Prosperity, Peace) over a period of time ranging from the implementation of the National Strategy to the post-pandemic. To do this, a set of representative indicators was created and a geographical sustainability assessment tool (SSAM) was used, which operates through a multicriteria analysis model perfectly integrated into a GIS environment. The results showed a strong regional variability and a radicalized North-South gap. Moreover, the monitoring between the different years (2017-2019-2021) showed the initially positive impact of the strategy, mainly due to the Planet dimension, but also the negative one that COVID-19 caused to all the regions, with different intensity depending on the dimensions considered.

Selection of suppliers in a bioindustry in the Amazon using the saw, topsis and promethee II methods combined with fuzzy logic

The production chain of bioindustry in the state of Amazonas is characterized by the use of products of Amazonian biodiversity and biotechnology in its production processes. An important difficulty faced by the region's biocompanies is identifying good suppliers of inputs of the Amazon biodiversity to attend to their industrial processes. The objective of this work was to propose a multi-criteria analysis model to support decision making for the selection of suppliers of a bioindustry. To this end, an exploratory research was conducted, with a quantitative approach, whose main procedures were: bibliographic research, case study and operational research. The procedure for selecting suppliers was structured in five stages, the results of which indicated supplier A2, through the individual methods, and supplier A1, through the combined methods, to be chosen. The use of fuzzy logic, combined with the proposed methods, was necessary to deal with judgments under high uncertainty. Due to the characteristics of the problem and the quality described in the literature, the Fuzzy-TOPSIS method for selecting suppliers of this nature is proposed.

Техническое обслуживание и ремонт цапф барабанной мельницы плавучего комплекса горного оборудования

Introduction. In order to develop promising deposits of non-ferrous metals in the Arctic zone, in particular the Pavlovskoye lead-zinc deposit on Novaya Zemlya, it is necessary to develop climate-saving geo-technologies for mining. In this connection, a concept of conservation geo-technology has been developed and proposed through the use of a specially designed floating complex of mining equipment, included together with the quarry equipment in a single technological chain for the extraction of ore raw materials and its processing into concentrate. However, for the full functioning of the concept of this geo-technology, it is necessary to carry out preventive maintenance and repair of mining equipment at the site of its operation on a floating complex. Research methods and materials. The methodological basis of the work is a systematic approach to the studied means of carrying out repair and restoration works of mining machinery and equipment, which includes both theoretical analysis and generalization of the results of fundamental and applied works of domestic and foreign authors, including methods and theories of designing technology for repairing metalworking and mining processing complexes, multicriteria analysis and simulation modeling. Research results. The article proposes a new technology for the implementation of repair work to restore the working surfaces of hollow loading and unloading support trunnions of hydrostatic sliding bearing units of a drum mill in cramped deck conditions of a floating complex of mining equipment for the development of deposits in the Arctic zone. The structure of the built-in mechanized modular machine tool complex is developed and presented, with the help of which the hollow support trunnions of the drum mill are directly machined according to the patented repair technology. Conclusion. It is shown that the use of the described repair technology by means of an embedded mechanized modular complex will reduce the complexity of the overhaul of the trunnions without the need to perform dismantling work to disconnect the mill drum body from the hollow trunnion caps, which has a positive effect on the accuracy of processing the working surfaces of hollow trunnions.

Flood risk assessment of Wuhan, China, using a multi-criteria analysis model with the improved AHP-Entropy method.

Floods are one of the most frequent global natural hazards resulting in significant human and economic losses. Therefore, assessing and mapping flood hazard levels is essential to reduce the severity of future flood disasters. This study developed an integrated methodology to evaluate flood risk using an improved Analytic Hierarchy Process (AHP) and Entropy Weight (AHP-EW) method based on cosine similarity (COS-AHP-EW). This method has more scientific results because it combines subjective and objective information. The proposed method's viability was then tested in Wuhan, China. Fourteen flood-inducing indicators were identified for the flood hazard, vulnerability, and restorability index system, with the indicator weights calculated using the COS-AHP-EW. This study utilized the Jenks method to develop the Wuhan flood risk map. We observed that the very high risk and high-risk areas covered 2.43% and 11.54% of the total study area and were mainly distributed in the highest economic and urbanization development and low-permeability districts, respectively. The validation with the historical waterlogging points reflected the accuracy and reliability of the COS-AHP-EW. The superiority of the proposed method was further verified by comparing it with single-evaluation methods (AHP and Entropy Weight) and another combined weight method (combined AHP-EW based on ideal point theory, namely, Ideal-AHP-EW). The comparison results indicated that the COS-AHP-EW was more accurate at predicting the risk in flood-prone area. Flood risk maps generated using the COS-AHP-EW could be applied to improve flood risk assessments, and the proposed method could be extended to other study areas to provide reliable flood management information.

Analysis of Water Harvesting Structures Sites Appropriateness Using GIS-Based Methodology: Diyala, Iraq, as a Case Study

Water harvesting is an effective technology that may be used to collect unused runoff, therefore meeting various water needs and mitigating droughts. The study area is experiencing severe water lacks, so the goal of this research is to find ideal locations for structures of water harvesting through the use of a geographical information system-based multi-criteria analysis model that employs fuzzy logic with the analytical hierarchy process model. According to the hydrology and geomorphic criteria of the research area, a suitability map for water harvesting was constructed, and 17 and 12 sites suitable for check dams and farm ponds, respectively, were suggested in the regions with high and very high classes. Thus, this study’s findings underline the significance of geospatial modeling in planning water facilities and addressing the water shortage issue in the study region.

Constructing smarter and more sustainable urban ecosystems: a dynamic analysis of challenges and initiatives

AbstractCities’ weaknesses have been revealed by their struggle to respond to current challenges (e.g., pandemic crises and population and urbanization exponential growth). Urban planners are thus increasingly concerned about implementing initiatives in their metropolises that favor a better present and future quality of life. In this context, cities need to become enablers of economic and social development and increased prosperity through the integration of technologies into projects promoting smarter and more sustainable urban ecosystems. These ecosystems are, however, highly complex due to their specificities and multifaceted nature, which makes analyzing them a difficult endeavor. Based on a constructivist and complementarity logic, this study sought to develop a multicriteria analysis model to support relevant decision-making processes in this study context. A panel of experts was recruited to create the analysis system using a combination of cognitive mapping and the decision-making trial and evaluation laboratory technique in an neutrosophic context. This approach overcomes various flaws identified in previous related research. The entire procedure focused on enhancing the experts’ learning through participation not only to structure the problem under analysis but also to identify and prioritize the factors and/or determinants of smartness and urban sustainability. The model provides a holistic, solid, and clear vision of the decision problem that fosters appropriate choices when creating and evaluating smart, sustainable urban ecosystems.

Enhancing urban public space through appropriate sustainable mobility policies. A multi-criteria analysis approach

Decision-making in the context of urban sustainability is a challenging problem for policy-makers, given its complex nature, demanding the compromise between different and, often, conflicting social, economic and environmental criteria. This multi-factor problem needs to be addressed in a holistic way, on the basis of an integrated transport and urban planning approach, through ad hoc planning for each different area. Land use and mobility policies are characterized by a high level of interaction, a fact that needs to be taken into account in urban and transport planning within the framework of sustainability. Effective land use policies may have a positive impact on sustainable mobility and vice versa: effective mobility policies may have a positive impact on sustainable land use in urban areas. Aiming at developing and testing via a case study a decision-support tool for policy-makers and decision-analysts to promote sustainable urban and transport planning, the application of two hybrid multi-criteria analysis models is proposed in this research work, in order to rank land use and transportation policies in the framework of urban sustainability, especially in terms of public space. The center of Thessaloniki (Greece), an urban area suffering from sustainable mobility and public space problems, is selected as a case study.

Identifying Suitability Rainwater Harvesting Zones in Diyala Watershed, Iraq, Using Multi-Criteria Analysis and GIS Modelling

The rising demand for water and the depletion of natural water resources, as well as the current environmental problems, have led to the need for the provision of additional quantities of water to enhance water resources and the sustainability of ecosystems. Water harvesting technologies are one of the most effective solutions to treat this issue. In this study, appropriate zones for rainwater harvesting in the Diyala Watershed were identified using the Geographic Information Systems-based multi-criteria analysis and fuzzy logic model. Seven criteria were selected: slope, stream order, rainfall, runoff, hydrological soil group, land use, and distance to roads. The map of suitability was categorized into five categories, ranging from very low to very high, and the map showed that the majority of high-suitability areas are situated in the southeast parts of the study area, while most of the regions of low suitability are located in the western and northern parts. Lastly, this study will contribute to the effective planning and administration of rainwater on a broader scale.

Planning for groundwater management using visual MODFLOW model and multi-criteria decision analysis, West–West Minya, Egypt

This study presents a planning model to assist decision-makers in implementing proposed sustainable development policies based on the government's development schemes. It focuses on the exploitation of groundwater from the Eocene aquifer in the West–West Minya region in the Western Desert of Egypt as one of the new development areas. The visual MODFLOW model is applied to serve as a base model for the study area's local modeling and assess the impact of operating scenarios on the groundwater aquifer. An optimal scenario for groundwater sustainability is achieved by considering the water meter consumption in the newly reclaimed area with a value of 6 m3/d for each acre to irrigate 3953.68 acres; the maximum drawdown of about 60 m is formed after 9700 days of simulation. The GIS multi-criteria analysis model is used to assess the impact of groundwater deficiency as a result of reclamation. Results of the groundwater model are merged as input layers in multi-criteria decision analysis, which include groundwater salinity, groundwater levels, aquifer transmissivity, and aquifer storativity. The prospective groundwater zones are categorized into most suitable (1584 km2, 9.9%), suitable (4592 km2, 28.7%), good (4784 km2, 29.9%), moderate (1488 km2, 9.3%), and unsuitable (3552 km2, 22.2%). It is recommended to optimize levels of groundwater withdrawal from the current or future drilling wells to achieve a balance between the use and the protection of water potential.

Multicriteria analysis model for foot-and-mouth disease risk classification in the state of Goiás - Brazil

ABSTRACT: Foot-and-mouth disease (FMD) is a viral disease that affects several animal species, including domestic and wildlife ones. The occurrence of an FMD outbreak can potentially cause a large negative impact on countries or regions’ livestock production and economy. Performed over several decades, mass herd vaccination has been the main strategy to control the disease. However, countries are beginning the stage of eradicating FMD, which involves suspending vaccinations. The present study carried out a risk classification for FMD occurrence in Goiás State, Brazil by evaluating and combining multiple risk factors involved in FMD introduction and dissemination. Data from 126,345 rural properties were collected and categorized by municipality. The risk factors were grouped into two modules and then scores for each module were obtained by adding and weighting the risk factors. These combined scores resulted in the final FMD occurrence risk score. Most of the municipalities, as well as the herds were found in the lowest likelihood levels. Variables linked to herd density and animal movement played a key role in the score composition. We believed that this model can be a useful tool in the decision-making process regarding actions and strategies related to FMD eradication.

Transport Infrastructure and Regional Development: A Survey of Literature on Wider Economic and Spatial Impacts

The main purpose of the paper is to provide an overview of methods used to research the relationship between transport infrastructure investments and regional development, with a focus on wider impacts both in the traditional economic context (wider economic impacts or WEIs) and—which is a methodological novelty proposed by this paper—in the spatial context (wider spatial impacts or WSIs). In terms of methodology, research may be conducted using the following methods: cost benefit analysis (CBA) and multi-criteria analysis (MCA), accessibility and potential models, econometric production function estimates, regional modelling, trade and input-output (IO) modelling, Land Use-Transport Interaction (LUTI) or spatial computable general equilibrium (SCGE) models. In the European Union, approaches based on cost-benefit analysis (CBA), or possibly multi-criteria analysis (MCA), continue to prevail. Notwithstanding the availability of a wide range of methods for quantifying socio-economic impacts, the European Union recommends that wider economic impacts at the regional and national levels be assessed by means of qualitative approaches. This being the case, it is recommendable for the European Commission to take broad-ranging action towards ensuring that the effects of transport infrastructure investments are assessed by means of a broader range of approaches.

Seismic performance of T-shaped CFST column to U-shaped steel-concrete composite beam joint

Both novel composite structures, special-shaped concrete-filled steel tube (CFST) column and cold-formed U-shaped steel-concrete composite beam with stiffened rebar truss (CUCB), have advantages of good mechanical behavior, appealing architecture, and convenient construction. In this study, a series of five half-scaled specimens of CUCB to T-shaped CFST column frame joints with vertical ribs were tested under cyclic loading. Different connection detail types were designed considering both mechanical and constructional aspects. The bearing capacity, stress distribution, stiffness degradation, energy dissipation capacity, ductility, and joint stiffness were evaluated to understand the seismic performance of these new joints. Experimental results show that joints with vertical ribs have favorable seismic performance and could be considered as rigid joint in a braced frame according to Eurocode 3. Based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, a multi-criteria analysis model for evaluating the joint performance was performed to determine the most effective connection detail considering the mechanical behavior and construction cost. As a result, the proposed novel joints are seismically feasible.

Usability of Cost systems in the Federal Public Sector

The objective of this study was to identify the perception of the usability of the Federal Public sector cost systems by the managers and cost information users. To this end, a survey was carried out with sector and sectionals of costs of the Federal Government, using a questionnaire that was validated by brainstorming and by focal group. The research quantitative data were obtained from the application of the multicriteria analysis model for decision support - Constructivist “Multicriteria Decision Aid - Constructivist” (MCDA-C). The results, generated in the MyMCDA-C software, showed that nine criteria reached the optimum points, reaching an excellent level of usability, which were considered to be very significant for achieving the objectives of using the cost systems. The greatest effort was for “cost methodology” and the lowest for “technology tools.” In practical terms, it was evident that the effort to seek a cost methodology relevant to the agency's objectives is greater than the technological tools currently available. The research also aimed to contribute based on literature to future studies on usability in the accounting sciences area and to subsidize public sector entities upon listing in this work criteria for implementing costs with a focus on usability.

Land Suitability Assessment for Maize (Zea mays L) Production using Integrated DEMATEL-ANP Model and GIS in the Foumbot Agricultural Basin (Cameroon Western Highlands)

This research recommends that the GIS and DEMATEL-ANP multicriteria analysis model should be extended to future works to select suitable lands for increasing maize production in other ecosystems.