Multi-criteria Evaluation Method Research Articles

STRATEGIC AND LEADING DOMINANTS OF OVERCOMING ECONOMIC - MANAGEMENT DEVIATIONS OF CONSTRUCTION PROJECTS USING FUZZY LOGIC

The article defines the directions of functioning of the construction industry and stakeholders of construction enterprises, reveals the main directions and peculiarities of the functioning of construction enterprises in the conditions of martial law (during the full-scale invasion of the Russian Federation on the territory of Ukraine) and substantiated directions of transformational development in the period of post-war reconstruction. The components of the theoretical-methodological platform for the formation and implementation of development management of construction enterprises have been developed using a methodical approach to the evaluation of strategic sets of the enterprise based on the improvement of the classical quantitative strategic planning matrix (QSPM, Quantitative Strategic Planning Matrix). As a conceptual basis for identifying such factors, the McKinsey “7S” model was used, according to which all factors are grouped according to the signs of belonging to the following components: strategy, skills, common values (corporate culture), structure, employees, systems and style. As a result of the study, the factors affecting the formation and implementation of the adaptive capacity of the construction enterprise to the transformational changes of the operating system are proposed: labor productivity in the studied period; the ratio of administrative expenses to wages in operating expenses; the share of employees with higher education in the total number of management personnel; experience of management personnel; the ratio of labor costs to wage costs. The processes of economic-mathematical modeling of the influence of system factors on the integral indicator of the level of transformational ability of the enterprise are determined. To achieve the goals, the work uses methods of strategic diagnostics and fuzzy methods of multi-criteria evaluation with the help of the Matlab Fuzzy Logic Toolbox application program package.

A STUDY ON THE USE OF BANKS FINANCIAL TECHNOLOGIES IN THE STATES OF THE EUROPEAN UNION

The article analysis financial technologies and their relevance and usefulness in the existing financial market. The work presents and analyzes the services (models) provided by financial technologies, they can be divided into payments, asset management, crowdfunding, lending, and the capital and insurance market. The main and most popular services provided by banks, which are related to financial technologies, are presented. A SWOT analysis of financial technologies is also presented, which shows the advantages and disadvantages of FinTech. The services provided by financial technologies are very diverse, they are provided by both ordinary companies and banks. This article focuses on financial technology that is provided by banks – internet usage: internet banking, number of ATMs, credit transfers in a state, percentage of population in a state, which shows how many people have a debit or credit card and whether those residents have received or made a digital transfer. In the third part, using multi-criteria evaluation methods: CRITIC and EDAS and performing cluster analysis, European Unions are compared and ranked.

Construction and optimization of ecological security patterns in the songnen plain

To address the ecological security issues in the Songnen Plain, this study constructs the ecological security pattern by using the Multi-Criteria Evaluation Method, Minimum Cumulative Resistance (MCR) model, and Circuit Connectivity Model. Results show that: 1) The ecological source areas were 66, 52, and 56 blocks in 2000, 2010, and 2020 respectively, which are composed mainly of forests, water bodies, and wetlands. The distribution of resistance values of the ecological resistance surface shows a gradually increases trend from the source areas to the outward surrounding regions. The high and low value areas are more dispersed, consisting with the overall spatial distribution; 2) The numbers of ecological corridors show a temporal declining trend from 178 in 2000 to 159 in 2020 with a reduction of 645.46 km in total length. Node areas are mainly distributed in the southwestern and central-eastern regions and its number decreased from 232 in 2000 to 229 in 2020. The sizes of obstacle areas are 74029.52 km2, 70203.72 km2, and 75529.72 km2 in the three periods; 3) The size of important ecological source areas has decreased by 5779.16 km2, the area of medium ecological source areas has increased by 11466.44 km2, and the area of general ecological source areas has increased by 9509.16 km2. The areas being classified as ecological conservation, ecological enhancement, ecological restoration, and ecological control are 30346.68 km2, 8480.56 km2, 51473.92 km2, and 122047.48 km2, respectively. The multiple spatial pattern optimization strategies are proposed based on the identified ecological source areas, corridors, node points, and other comprehensive ecological security patterns. It not only provides practical reference for the ecological restoration and ecological protection in the Songnen Plain, but also can be used for the ecological security pattern investigations in other study regions in the world.

Potentials and opportunities of solar PV and wind energy sources in Saudi Arabia: Land suitability, techno-socio-economic feasibility, and future variability

Solar and wind energy sources hold significant potential to meet the escalating energy demand in Saudi Arabia sustainably. This research aims to assess the feasibility and prospects of deploying solar photovoltaic (PV) and wind energy systems in Saudi Arabia (SA). The study adopts a comprehensive approach, encompassing spatial analysis of land suitability, techno-socio-economic feasibility studies, and prediction of renewable energy (RE) resource variability and trends using machine learning techniques. Geographical Information System (GIS) spatial analysis is employed to identify suitable areas for establishing solar PV and wind farms based on multi-criteria evaluation methods. Techno-socio-economic feasibility analysis of solar PV and wind energy systems, under various configurations and scenarios, is conducted using the System Advisor Model (SAM) tool. Furthermore, a Support Vector Machine (SVM) machine learning algorithm is developed and deployed to forecast Global Horizontal Irradiation (GHI), wind speed, and influential weather parameters at different locations in SA. The projections of these variables derived from global climate models are utilized to analyze prospects and variabilities. The land suitability analysis identified four optimal locations for large-scale solar PV fields in Tabuk, Al Madinah, Makkah, and Riyadh provinces. Additionally, four promising wind farms were found in Al Madinah, Makkah, Riyadh, and Eastern provinces. The analysis also identified one location in Al Jouf province suitable for hybrid systems combining solar PV and wind energy. The techno-economic assessment revealed that wind farms performed best overall, achieving a capacity factor of 42.6 % in Al Madinah province. Although current tariffs render projects economically unviable, solar PV, wind energy, and hybrid solar PV-wind technologies are economically feasible in SA at Power Purchase Agreement (PPA) rates above $32.8/MWh, $26.1/MWh, and $50.6/MWh, respectively. The social development analysis estimated potential job creation from solar PV and wind energy deployment under different scenarios from 2020 to 2060, indicating that more ambitious climate targets could translate to millions of renewable energy jobs. The SVM model predicted solar irradiance with an R-squared value of 0.893. The CMIP6 model was then used to project the GHI for SA in 2049, suggesting an increase of approximately 19 %. Wind speed is also expected to rise roughly 5 % over the same period. The integration of GIS spatial analysis, techno-socio-economic modeling, and machine learning-based forecasting provides comprehensive insights into harnessing solar and wind energy in SA. This study facilitates evidence-based planning and risk assessment, crucial for a sustainable energy transition. The insights and roadmap derived from this research can inform policy frameworks, support the United Nations Sustainable Development Goals (UNSDGs), and attract private investments for RE development in SA. Consequently, this study establishes solar and wind energy as viable and promising solutions for meeting SA's growing energy demands sustainably, while minimizing the associated environmental impact.

Spatial Planning of Marine Protected Areas (MPAs) in the Southern Caspian Sea: Comparison of Multi-Criteria Evaluation (MCE) and Simulated Annealing Algorithm

Protected areas are referred to around the world as the basis of conservation strategies. Designation of marine protected areas (MPAs) is to preserve marine biodiversity and protect species, habitats in the seas, and oceans. The simulated annealing algorithm (SAA) with other algorithms (swap iterative improvement, normal followed by two step, two step iterative improvement, and normal iterative improvement) in MARXAN conservation solutions software and the multi-criteria evaluation (MCE) method were used to locate MPAs in the Southern Caspian Sea. Then, four methods were examined for site selection that include: (1) Simulated annealing algorithm, (2) MCE with zonal land suitability (ZLS), (3) MCE with compactness and contiguity, and (4) combined method of multi-criteria evaluation with spatial constraints and a simulated annealing algorithm (improved MCE). In the MCE method, we applied different weighted scenarios to locate MPAs. The criteria for determining the desired regions of MPAs included 12 factors gathered in three groups, including: (1) Ecological criteria (distribution of fish Huso huso, Acipenser persicus, Acipenser stellatus, Rutilus frisii kutum, and Alosa braschnikowi; location of coastal protected areas, distance from coastal rivers (Coastline), distance from estuaries and deltas); (2) Physical criteria (distance from the coast, shore sensitive areas); and (3) Socio-economic criteria (distance from densely populated coastal cities, distance from industries near the coast). The results of comparing the algorithms in MARXAN 4.0.6 software showed that the simulated annealing algorithm has a better ratio of border-length/area than other algorithms. Also, the combined method of MCE (improved MCE) selects the best protection patches in terms of location, taking into account the seascape ecology metrics (e.g., patch compactness, edge density, normalized entropy, area metric for patches). Moreover, the results of the comparison of four methods for proposing MPAs based on seascape metrics showed that the combined method of MCE considers a protection network with more contiguity and compactness than the simulated annealing algorithm. The use of seascape ecology can help to preserve and create larger and denser patches in the arrangement of protective areas, because such a selection of protective areas is nature-inspired and can be more bold and appropriate in the course of conservation planning.

Participatory evaluation of cultural heritage adaptive reuse interventions in the circular economy perspective: A case study of historic buildings in Salerno (Italy)

Adaptive reuse of cultural heritage can be a valid strategy to recover heritage buildings in a state of abandonment or underuse, as well as to implement the circular economy model in cities and regions, contributing to the achievement of climate objectives, to social cohesion, wellbeing and quality of life, making cities more attractive, safe, sustainable and resilient. The aim of this paper is to develop and test an ex-ante evaluation methodology to support participatory decision-making processes for the adaptive reuse of cultural heritage according to the circular economy perspective. A multidimensional and multicriteria evaluation framework was experimented in the city of Salerno, Italy, to assess alternative solutions for the adaptive reuse of four large historic buildings in abandonment, and identify a satisfying solution based on interactions with local stakeholders. The TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) multi-criteria evaluation method was used to compare adaptive reuse project alternatives including stakeholder objectives and preferences. Starting from 14 adaptive reuse proposals, the participative evaluation methodology supported stakeholders in the identification of 4 preferable solutions further developed and co-designed, as well as in the search of a final satisfying solution engaging diverse stakeholders groups. Moreover, operational circularity criteria for the adaptive reuse of cultural heritage were identified. The results of the study show the potential of Multi-Criteria Decision Analysis (MCDA) mixed with participative methods for co-design and co-evaluation to support inclusive decision-making processes for circular adaptive reuse of cultural heritage.

Modelling malaria vulnerability hotspot by using geospatial techniques: the case of Kindo Koysha Woreda, Wolaita Zone, Ethiopia

Malaria is a serious, acute disease spread by female Anopheles mosquito bites. Malaria is an epidemic in the Wolaita Zone, affecting 85% of the population despite the implementation of effective prevention and control measures in the area’s public health services. The main objective of this study is to apply geospatial techniques to environmental, socioeconomic, and epidemiological parameters that increase certain conditions for malaria incidence to identify malaria vulnerability hotspots using a multi-criteria evaluation method. The malaria vulnerability hotspot map is identified by using AHP and the malaria hotspot identification algorithm. The findings show that the research area is 51% very high and highly vulnerable (224.14 km2), 26% moderate (116.560 km2) and 23% low vulnerable (103.600 km2). The western part of the area, which is near the Omo River and has low elevation, is highly vulnerable to malaria incidence. Reliable malaria vulnerability hotspot maps are critical for estimating the scope of the problem and, consequently, the resources required to combat malaria.

ОЦЕНКА ЭКОЛОГИЧЕСКОЙ БЕЗОПАСНОСТИ И ЭНЕРГЕТИЧЕСКОЙ ЭФФЕКТИВНОСТИ ТРАНСПОРТНЫХ СРЕДСТВ, ОБСЛУЖИВАЮЩИХ МАРШРУТЫ ГОРОДСКОГО НАЗЕМНОГО ТРАНСПОРТНОГО КОМПЛЕКСА

The urban passenger transport complex is the most important part of the infrastructure of modern cities and provides a number of key functions. The condition for the effective operation of the transport complex is the balanced development of the subsystems included in its structure, which in turn necessitates the formation of a methodological framework that determines the conditions for such development. Based on the indicated provisions, the purpose of the study is formulated, which is to increase the efficiency of the operation of vehicles serving the routes of the urban ground passenger transport complex, based on the results of an assessment of their environmental safety and energy efficiency. To achieve this goal, it is necessary to solve a number of tasks: – study and analysis of the content of research papers, regulatory and technical documents in the field of environmental safety assessment of energy efficiency of vehicles; – development of a methodology for assessing and comparative analysis of environmental safety and energy efficiency, vehicles serving urban public transport routes; – assessment of environmental safety of various categories of vehicles serving the routes of the urban ground passenger transport complex; – generalization and analysis of the results obtained, formulation of conclusions and practical recommendations. During the study, an approach was used that assumes: modeling of energy consumption parameters of vehicles implementing various technologies of fuel and energy supply and a comparative assessment of indicators determining their energy efficiency and environmental safety in traffic conditions on urban passenger routes. Based on the implemented approach, the methods of system and statistical analysis of the initial information, mathematical modeling and methods of multi-criteria evaluation of the results are used in the work. The main result of the study is the numerical values of the indicators of energy efficiency and environmental safety of vehicles implementing various technologies of fuel and energy supply in the conditions of urban ground passenger transport complex, which is the scientific novelty of the study. The use of the obtained values in assessing the efficiency of passenger transportation by vehicles of various categories allows for the formation of a fleet of vehicles based on the results of a multi-criteria analysis. One of the directions of further research involving the use of the results obtained is the development of a comprehensive methodology for determining the optimal structure and coordinated formation of subsystems that make up the urban ground passenger transport complex.

МЕТОД МНОГОКРИТЕРИАЛЬНОЙ ОЦЕНКИ ЭФФЕКТИВНОСТИ ТЕХНИЧЕСКИХ СРЕДСТВ В ОРГАНИЗАЦИОННО-ТЕХНИЧЕСКИХ СИСТЕМАХ

Evaluation of the efficiency of technical means is an important practical task at the stage of selecting their composition when designing complex organizational and technical systems. The author's method of multicriteria evaluation of technical means efficiency on the basis of dimension analysis is proposed, which allows to take into account many of their private characteristics. This method allows solving the problems of determining the quantitative values of generalised indicators of efficiency and effectiveness of technical means and, on their basis, selecting the preferred option for inclusion in the structure of organisational and technical systems. A practical example of using the method to select sensors in the synthesis of fire protection system of the object is presented.

Assessment of the Lithuanian Pig Farming Sector via Prospective Farm Size

Scientists, politicians, and practitioners are debating the current structure of pig farms in Lithuania, as medium and small farms have almost disappeared over the past decade. The debated problem is whether the revitalization of medium and small pig farms would sustainably contribute to self-sufficiency in pork production. Therefore, this research aims to determine which farms in terms of size could offer the best prospect for Lithuania. In order to achieve this aim, the multicriteria evaluation method TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) was used. The production and economic indicators of the Lithuanian pig farming sector in Lithuania and in the context of the selected EU countries of Belgium, Denmark, Germany, Estonia, Spain, France, Latvia, Netherlands, Austria, and Poland were analyzed. The main research period was 2004–2022. The multicriteria evaluation led to the conclusion that Danish pig farms were the best-managed. Large industrial farms were found to dominate in that country. Large pig farms (approximately two thousand sows) appeared as the best prospect in Lithuania: they took first place in the years examined (2016–2021). The criterion estimate of their assessed indicators was much higher than that of the medium (100 sows) and small (20 sows) farms. The main reasons are significantly higher labor productivity, lower cost, lower price, and better production indicators. Large pig farms generate relatively higher incomes and can meet the increasing environmental requirements and devote a larger part of the income to wages. Further research should consider the European Green Deal and the Farm to Fork Strategy, which are of great importance to farms and policymakers.

INTEGRATION OF MIGRANTS INTO THE COUNTRY’S SOCIAL ENVIRONMENT: THE CASE OF LITHUANIA

Migration is one of today’s most sensitive and relevant topics. In 2022 alone, 32.5 million people worldwide will have left their country due to war, political instability, economic hardship, climate change, and other reasons. In recent years, the constantly growing flow of migrants to developed countries poses increasing challenges to the institutions and organizations of those countries, which are looking for new ways of integrating migrants into the social environment. It is difficult for state institutions that do not have the right tools to assess the integrity of the state, and it is difficult to control the ongoing migration processes and quickly make decisions regarding the increased flows of migrants, which could be solved promptly with minimal use of resources. One of the most important solutions for overcoming the challenges of migration is using a dynamic complex instrument that would allow us here and now to identify the causes of changes and efficiently mobilize the necessary resources to solve the challenges of migration that are usually not planned. The article aims to form a complex evaluation instrument to integrate migrants into the social environment. To achieve the goal, a systematic, comparative analysis of concepts and methods published in the scientific literature, statistical processing, and multi-criteria evaluation methods (COPRAS), and the method of determining weight coefficients (CRITIC) is applied.

Assessment of the economic security of Baltic port cities’ competitiveness

City competitiveness is a complex product of local and international conditions, local characteristics, social and economic superstructure, and the actions of individual companies. Although many scientific studies have examined the country’s and urban competitiveness, the competitiveness of port cities still needs to be assessed comprehensively, taking into account their crucial economic role. The purpose of this paper is to evaluate the competitiveness and economic security of the Baltic port cities (Klaipėda, Riga, and Tallinn). Statistical processing and multi-criteria evaluation methods (SAW, COPRAS, and TOPSIS) were chosen to achieve this goal. The comparative analysis showed that the population change in port cities is not significant for the final result of the competitiveness assessment, and the unemployment rate in port cities is lower than in the country. The assessment of the competitiveness of port cities from the point of view of economic security shows (after checking such indicators as unemployment rate, company income, and infrastructure) that Tallinn is the most competitive port city according to the three multi-criteria evaluation methods, while Klaipėda is the least competitive. The assessment was carried out in three stages to monitor changes in the situation of port cities, compared to changes in a certain indicator and the costs of timely solutions or the improvement of the city’s position in relation to other cities.

Mapping The Location of Flood Shelters in Demak Regency using The Spatial Multi Criteria Evaluation Method

Floods are the most common disasters in the world and severely disrupt lives and livelihoods. Furthermore, the developing countries, especially Indonesia, around 241 flood events in early 2023. The World Bank’s through its Climate Change Action Plan 2021-2025, aims to support Green, Resilient, and Inclusive Development, in pursuing poverty eradication and shared prosperity with a sustainability lens. In the action plan, there are actions to identify and prioritize mitigation and adaptation activities to this effect. In connection with Flood Risk Management where there is no flood shelter location Demak Regency, this study aims to research location using the Spatial Multi Criteria Evaluation method by using the Geographic Information System. Geographic Information System can provide a precise and an effective mapping to mitigate the flood disaster. The Flood shelter can help disaster preparedness activities by minimizing casualties in Demak Regency. Based on the identification results, it was found that there were 36 main points and priority flood shelters in the form of worship facilities and educational facilities.

GIS-Based Multi-Criteria Evaluation (MCE) Methods for Aquaculture Site Selection: A Systematic Review and Meta-Analysis

With the growing demand for aquatic products, aquaculture has become a prominent means of meeting this demand. However, the selection of suitable sites for aquaculture remains a key factor in the success of any aquaculture operation. While various methods exist for site selection, geographic information system (GIS)-based multi-criteria evaluation (MCE) methods have emerged as the most widely utilized approach to identifying potential aquaculture sites. Following the guidelines of the preferred reporting items for systematic reviews and meta-analyses (PRISMA), this paper presents a systematic review and meta-analysis of GIS-based MCE methods used in aquaculture sites selection. The objective of this study is to offer a comprehensive overview of existing research in this field and develop a general model for selecting sites for fish and shellfish aquaculture. The main findings indicate a growing number of studies utilizing GIS-based MCE in aquaculture site selection in recent years, with Asia being the leading continent in terms of publications in this domain. Among the journals publishing in this field, the Aquaculture journal stands out as the top publisher. Using consistent criteria across the reviewed studies, two models have been generated, each consisting of four sub-models: water quality, soil quality, infrastructure, and socioeconomic factors; and topography, environment, and physical parameters. These models can aid future researchers and assist decision-makers in identifying optimal locations for aquaculture development.

Land Suitability of Urban and Industrial Development Using Multi-Criteria Evaluation (MCE) and A New Model by GIS in Fasa County, Iran

Land use planning is a science that specifies the optimized use of land based on ecological and socioeconomic characteristics. In many parts of Iran, the selection and management of land use (development, especially) is performed regardless of land capability, which causes disinvestment and reduces the environmental capacity. The main objective of this study is to evaluate and reform the ecological model of urban, rural, and industrial development in the study area. This study was conducted in Fasa County in the southern part of Iran, and the investigated methods included Weighted Linear Combination (WLC) or Multi-Criteria Evaluation (MCE), with two views, without limitation and with limitation, and the proposed geometric mean method through the integration of maps in GIS. The results showed that the geometric mean evaluation model (with kappa = 0.69) is the best and easiest compared to other models in the estimation of environmental capability. It should be mentioned that the lowest precision (with kappa = 0.59) between the methods was observed in the MCE method without a limiting factor, and it is clear that the limiting factor has a decisive role in assessing ecological capability and increasing accuracy. It is concluded that the proposed geometric mean method, due to the simplicity and high accuracy of the calculations, has a significant contribution to increasing efficiency and reducing the costs associated with the assessment of ecological capability.

A model for forecasting the volume of the entertainment services market under non-determinative conditions

The subject matter of the article is the theoretical-methodical and applied principles of modelling and forecasting indicators of the market volume of entertainment services. The goal of the work is to find a mechanism that will allow determining the volume of subscribers, taking into account exogenous variables, especially during socially unstable situations, such as a pandemic, war, cataclysms, etc. The following tasks are solved in the article: formation of criteria for companies for which the created mechanism is planned to be applied; review of basic autoregression models; determination of factors that should serve as an external influence when predicting the number of subscribers; creation of a multi-criteria choice problem; conducting experiments according to the proposed methodology to test the proposed hypotheses and systematize the obtained results. The following methods are used: analytical and inductive methods for forming factors of external influence and description of target companies; expert evaluation method for determining the most influential external indicators; experimental method, statistical methods of processing time series and methods of multi-criteria evaluation to determine the most effective autoregression model. The following results were obtained: the factors of external influence were formed: As external variables, it was decided to choose: the dynamics of the incidence of coronavirus, the rate of change in the global gross domestic product, the change in the S&P500 index, and the news from the world's largest news agencies converted into numerical form; a set of criteria for comparing models was created, saving forecasting time, accuracy, the possibility of taking into account external influence and the specificity of taking it into account; it was determined that the most accurate model is autoregression of the moving average, which at the same time is the most effective model given the created problem of multi-criteria selection; the similarity of the obtained results of experiments with global and domestic research is established. Conclusions: the use of analytical and inductive methods in combination with an experimental approach made it possible to obtain an effective (with an accuracy of more than 95%) mechanism for forecasting the market volume of companies that operate in the film industry and have a signature pricing model. The obtained result will allow players with a smaller market volume not to lose their audience due to the instability of the external environment, and, accordingly, will stimulate the development of the industry in general.

The Carbon Footprint of Thermal Insulation: The Added Value of Circular Models Using Recycled Textile Waste

The goal of climate neutrality by 2050 drives the building sector towards stricter control of processes and products, leading to a substantial reduction of embodied carbon throughout the life cycle. Many of the most used insulation materials have a high carbon footprint, mainly due to the production phase (from cradle to gate). The need to reduce these impacts has led to the implementation of materials whose predominant raw material is recycled material in order to reduce the embodied carbon. The contribution presents the results of a research work that analysed the potential of insulation materials obtained from textile waste, evaluating not only their energy performance but also, above all, their environmental impact in terms of carbon footprint. It starts from a state-of-the-art analysis of the main traditional and new-generation thermal insulation materials, not only in relation to performance but also to environmental impacts, in order to investigate the opportunities offered using insulation materials designed according to circular models (10R) and produced with industrial and/or post-consumer waste fabrics, through a carbon footprint comparison. To support the choice of this type of insulation, a multi-criteria evaluation method is proposed through which the comparative analysis of the most significant insulation products selected is carried out.

Machine Learning–Based Prediction of Irradiation-Induced Swelling from Synergistic Effects of Helium and Hydrogen

Understanding irradiation-induced degradation processes of nuclear structural materials is essential for creating methodologies and procedures for nuclear reactor safety. Due to the time- and resource-intensive property of both experiments and multiscale simulations of irradiation damage, the trial-and-error approach is completely inefficient. Recently, machine learning techniques have been employed to predict the properties of reduced activation ferritic martensitic (RAFM) steels, such as yield strength and elongation, as well as irradiation embrittlement in steel pressure vessels, with encouraging progress. In this work, void swelling is predicted using a machine learning method for the first time, taking into account the synergistic effects of displacement damage, helium, and hydrogen. Assisted by the analysis of feature engineering, seven machine learning models are trained and compared by multicriteria evaluation methods. Finally, the parameter-optimized gradient-boosting model is selected as the mapping function with the highest accuracy and universality to predict void swelling. In particular, the dependence of the void swelling and the injection amount of helium and hydrogen in the continuous parameter variation range is predicted beyond the existing experimental data. This work demonstrates the feasibility of machine learning to predict material irradiation damage by synergistic effects and has practical significance in nuclear material optimization and reactor safety.

Application of GIS and fuzzy sets to small-scale site suitability assessment for extensive brackish water aquaculture

ABSTRACT The rapid expansion of extensive brackish water aquaculture (BA) in Indonesia has created an urgent need to develop effective and reliable methods to evaluate and select sites suitable for aquaculture development. The lack of supporting spatial data at appropriate scales has limited the application of GIS-based multi-criteria evaluation methods (MCEs) in Indonesia. This study presents alternative fuzzy-based Geographic Information System (GIS) methods to evaluate and select sites suitable for extensive brackish water aquaculture. This study successfully produced fuzzy set maps from a water availability sub-model, a land conversion sub-model and a green belt buffer zone sub-model. With grades of membership, the fuzzy set maps provide smooth class boundary representation, which creates more options for decision-making than a map classified with crisp logic. Combining these sub-models produced an overall site suitability map at the scale of 1:50,000 for the study region. This final suitability map effectively excluded more than 95% of the unsuitable area for BA. This broad-scale site suitability assessment approach is a helpful planning tool to promote Indonesia’s sustainable development of extensive brackish water aquaculture. It identifies possible conflicts in land uses and considers conservation issues early in the planning process. The output can be used to scope research areas for more detailed investigations in countries where BA is a vital livelihood.

Multi-criteria thermo-economic analysis of solar-driven tri-generation systems equipped with organic Rankine cycle and bottoming absorption refrigeration and Kalina cycles

Optimal thermo-economic integration of renewable energy sources with multi-generation energy systems is a prime research topic today. The present study proposes a multi-criteria evaluation method of such integration, based on combined heating and power (CHP), and combined cooling and power (CCP) scenarios, for three different solar intensities. Three novel solar-driven tri-generation systems are selected. They include different organic Rankine cycle (ORC) architectures and a Kalina cycle system (KCS) and a double-effect absorption refrigeration cycle as bottoming cycles. Evaluation of the tri-generation systems, both with and without the KCS system, indicates a performance improvement of up to 23% in various thermoeconomic characteristics when the KCS system is present. Selection of the suitable tri-generation system for each condition and optimization of the working fluid are carried out based on a multi-attribute decision-making method. P-xylene is found as the optimal organic working fluid for ORC and ORC (ORC integrated with internal heat exchanger) based systems, and benzene for the regenerative ORC-based system in both CHP and CCP scenarios. Multi-criteria analysis shows that ORC-based system outperforms other systems with net outranking flow of 0.44 (0.39) for CHP (CCP) application. The optimal configuration gives 95.6 M$ and 1.99 years for net present value and dynamic payback period, and 83.03% and 34.55% for energy and exergy efficiencies, respectively.