Decision Analysis System Research Articles

Literature review of food insecurity in the Sahel from an interdisciplinary perspective

ABSTRACT This paper fills a gap in the literature by consolidating existing literature on food insecurity in the Sahel region. We explore the literature by considering the four primary characteristics of food security, namely; food accessibility, availability, utilisation, and stability. We further examine three crucial factors impacting food insecurity – climate change, conflict, and COVID-19 - as identified by the UN. This paper aims to provide researchers with an interdisciplinary perspective to build decision analysis systems through multidimensional exploration. We discuss the contributions as well as the limitations of this research. In general, our literature review also contributes to global as well as region-specific food security goals.

Planning shared mobility hubs in European cities: A methodological framework using MCDA and GIS applied to Barcelona

In the move towards sustainable urban mobility through seamless intermodality, European cities are faced with the possibility of implementing shared mobility systems. They constitute an opportunity to create new urban hubs, considered as nodes of intermodality and places of urban intensity. In order to effectively plan the future locations of shared mobility hubs, this paper outlines the methodological framework that sustains the design of a new decision-support tool, the so-called Mcda2MobilityHub (M2MHub),11Link to the M2MHub tool, which is available as an open plugin for QGIS: https://github.com/natrouk/Mcda2MobilityHub-desicion-support-tool_QGIS-plugin. using Multi-Criteria Decision Analysis (MCDA) and Geographic Information Systems (GIS). For this purpose, the analysis of existing literature and interviews with local authorities and transport operators, led to the identification of six main location criteria (mobility, compactness, diversity of uses, profile of potential users, spatial configuration and environment). The criteria weights were calculated using the Analytic Hierarchy Process (AHP) and the framework was applied to the case study of the city of Barcelona. The results obtained are presented in the form of heat maps, highlighting the flexibility of the decision-support tool to transform open data into appropriate indicators and detailed maps. This output can be used to support future policies for planning shared mobility hubs as places for convenient multimodal transfers, which also enable social activities and improve the quality of life in European cities.

A spatial decision support system for multi-dimensional sustainability assessment of river basin districts: the case study of Sarno river, Italy

Effective management of the complex Socio-ecological systems (SES) of the river basin, influenced by a range of social, economic, and environmental variables, requires multi-purpose Spatial Decision Support Systems (SDSSs) to identify and select balanced and sustainable regeneration scenarios. In many cases, the lack of cooperation between administrative institutions and the low level of participation of the stakeholders involved are the main obstacles to effective planning and regeneration practices and call for new forms of governance. However, to address these critical issues, few studies use quantitative approaches to assess the multidimensional resources of river basins in an integrated perspective in terms of their capacity to activate cooperation networks between river-crossed cities. This study aims to suggest a methodological approach combining Multi-Criteria Decision Analysis and Geographic Information Systems to achieve integration in pursuing sustainable regeneration pathways for a river basin district, analysing the case study of the Sarno River, composed of 20 administrative units, in Southern Italy. The specific purpose is to provide decision-makers with an SDSS to evaluate sustainability scenarios based on the multi-dimensional performances of River Basin District Units (RBDU). The results delivered four partial rankings of RBDU related to social, cultural, ecological, and economic scenarios and one overall ranking for an integrated sustainability scenario. Each ranking includes a clustering of municipalities according to three classes: Leader, Link and Follower. The outcome is twofold: to provide decision-makers with recommendations for supporting governance models based on sustainability pathways and to suggest valuable methods and tools for dealing with the spatial misfits, considered as the mismatch between the physical boundaries of a natural system and the management area of an organization.

Engineering Economic Systems: Past, Present and Future

At Stanford, engineering economic systems emerged as a discipline in the late 1960’s. The department’s curriculum had four central areas: decision analysis, optimization, economic sciences, and dynamic systems. The emphasis was on both practice and theory. The Management Science and Engineering Department at Stanford (MS&E), founded in 2000, is an outgrowth of the former Engineering Economic Systems Department. MS&E focuses on the codesign of engineering platforms and social systems in the 21st century, at scale and with pervasive data. The goal is to understand, design, implement, and control large-scale, integrated systems of people and machines. The intellectual spectrum ranges from analytics and computation to social and behavioral sciences. This article describes examples of past and present projects in the areas of energy, education, the economy, the environment, and health. Looking to the future, we are likely to see the continual emergence of new technologies, increasing amounts of data, increasing levels of connectivity, advances in computing, ubiquity of machine learning and artificial intelligence, and increasing importance of the need to address social and environmental problems. These will lead to new ways of analyzing problems and rich new opportunities for the tools of engineering economic systems to have impact.

SPATIAL CRITERIA FOR INDUSTRIAL AREA: SUSTAINABLE DEVELOPMENT STRATEGY IN SANGIRAN CULTURAL HERITAGE ZONE, GONDANGREJO DISTRICT

<span>Gondangrejo District is a suburb (peri urban) of Surakarta City with significant industrial growth in Karanganyar Regency. The driving factor of the development of the Gondangrejo District is the relocation of urban activities in Surakarta City. Gondangrejo District is an area of deconcentration of industrial activities because of its location directly adjacent to Surakarta City. A comprehensive site selection analysis is essential for industrial siting that supports sustainable builders. We select the optimal site for the industrial area by considering various criteria and inhibiting factors using GIS-based MCDA. Most suitable for industrial sites with GIS and AHP to build industries in The Gondangrejo District. This study aims to determine the most optimal industrial area by considering various appropriate criteria using multi-criteria decision analysis (MCDA) and geographic information system (GIS) methods. Based on the criteria used, namely proximity to roads, distance from rivers, distance from settlements, physiology, and population density with the same weight of 20%, a suitable location for the industrial area with a linear pattern or extending from east to west in the Gondangrejo District. Based on the same criteria with different weights from the results of the AHP analysis, suitable locations for industrial sites are Dayu Village, Rejosari Village, and Wonosari Village, which form a centering pattern. The study results found that the optimal industrial areas in Gondangrejo District are Dayu Village, Rejosari, and Wonosari. The results of the suitability of this industrial area can be used by decision-makers in the development planning of the Gondangrejo District.</span>

Evaluation and Design of Employment Decision Analysis System Based on Artificial Intelligence

Evaluation and Design of Employment Decision Analysis System Based on Artificial Intelligence

Applying Decision Analysis and System Dynamics Community Governance in the Evaluation of Juvenile Delinquency Prevention Strategies

Abstract From the perspective of juvenile delinquency prevention theory, this paper explores the current situation of juvenile delinquency in rural areas of W County and the mechanism of relevant functional departments in local community governance based on the questionnaire survey method. Then, six juvenile delinquency prevention service programs are selected as the object of evaluation research, and the intelligent decision analysis system of system dynamics is used as the tool of evaluation research to evaluate the six juvenile delinquency prevention programs systematically and comprehensively. The following conclusions were obtained after the analysis. The crime rate of rural youths in County W is as high as 15.8%, with a wide range of crimes. 81.6% of the relevant departments in community governance did not establish rural juvenile records, and about 13% of the departments did not conduct crime prevention training. The Green Clay People Juvenile Crime Prevention Program, which uses social connection theory as a strategy, has an evaluation value of 0.242, and the completion rate of the agreed service indicators specified in the contract is more than 100%. The overall evaluation of the six programs was 87% satisfied. Therefore, the intelligent decision analysis system in this paper has been well applied in the evaluation of juvenile crime prevention strategies, with the progress and development of society, and will occupy an important position in the future for a considerable time.

Framework for integrating multi-criteria decision analysis and geographic information system (MCDA-GIS) for improving slums interventions policies in Cairo, Egypt

Decision analysis is a key aspect in improving slums intervention strategies utilizing a variety of tools to evaluate all relevant information that support decision-making process for dealing with the complexity of slums interventions policies. This paper presents a framework integrating Multi Criterion Decision Analysis (MCDA) with (GIS) based decision support tool to quantitatively assess land suitability for site relocation of an urban slum site utilizing Analytical Hierarchy Process (AHP), which is commonly used for fastest growing decision-analytic techniques in several disciplines for the determination of various aspects weights. Herein Batn Al Baqara region (which is located in south of Cairo) was selected as study area to be relocated as it was considered among the most difficult to deal with, three proposed relocation sites were selected and analyzed using MCDA-GIS Model. Twelve different criteria were utilized to evaluate the degree of suitability of the relocation sites. A five degree of suitability were employed according to the different criteria scores for each site. The results supported that Al Asmarat is the most suitable site for the relocation of slum since it achieved the highest evaluation score (84.92 %) when the model was applied to the relocation sites.

Application of Data Mining Algorithms in Power Marketing Predictive Analytics

Abstract The electric power industry has accumulated a large amount of historical data, and the analysis based on data mining can provide an effective reference for the electric power marketing of enterprises. In this paper, according to the analysis architecture of electric power marketing and its functional modules, the electric power marketing analysis system based on Bayesian algorithm is constructed through data extraction and transformation, modeling of Bayesian network, and simulation operation. At the same time, for the shortcomings of Bayesian algorithm with the large error of classification results under the condition of strong sample correlation, mutual information is introduced to modify the number of Laplace smoothing. The MI-NB model predicts the probability of electricity risk for company A to be 60% and the probability of electricity risk for company B to be 40%, with an error rate of 9.65% and 8.37%, respectively. In line loss rate analysis, the MI-NB model predicts an average line loss rate of 60.46% for station 1 and 60.43% for station 2, both in the high line loss rate range. The Bayesian algorithm based on mutual information can improve the practicality and intelligence of the power marketing decision analysis system, which makes the decision management of power supply enterprises more scientific and reasonable, and is of great practical significance in reducing the operational risk of enterprises.

Retracted: The Evaluation and Its Key Influencing Factors Analysis of “Double First-Class” Universities’ Teaching Efficiency in China Based on SBM-DEA and Its Visual Decision Analysis System Development

Retracted: The Evaluation and Its Key Influencing Factors Analysis of “Double First-Class” Universities’ Teaching Efficiency in China Based on SBM-DEA and Its Visual Decision Analysis System Development

Poly- and Perfluoroalkyl Substances (PFAS): Do They Matter to Aquatic Ecosystems?

Poly- and perfluoroalkyl substances (PFASs) are a group of anthropogenic chemicals with an aliphatic fluorinated carbon chain. Due to their durability, bioaccumulation potential, and negative impacts on living organisms, these compounds have drawn lots of attention across the world. The negative impacts of PFASs on aquatic ecosystems are becoming a major concern due to their widespread use in increasing concentrations and constant leakage into the aquatic environment. Furthermore, by acting as agonists or antagonists, PFASs may alter the bioaccumulation and toxicity of certain substances. In many species, particularly aquatic organisms, PFASs can stay in the body and induce a variety of negative consequences, such as reproductive toxicity, oxidative stress, metabolic disruption, immunological toxicity, developmental toxicity, cellular damage and necrosis. PFAS bioaccumulation plays a significant role and has an impact on the composition of the intestinal microbiota, which is influenced by the kind of diet and is directly related to the host's well-being. PFASs also act as endocrine disruptor chemicals (EDCs) which can change the endocrine system and result in dysbiosis of gut microbes and other health repercussions. In silico investigation and analysis also shows that PFASs are incorporated into the maturing oocytes during vitellogenesis and are bound to vitellogenin and other yolk proteins. The present review reveals that aquatic species, especially fishes, are negatively affected by exposure to emerging PFASs. Additionally, the effects of PFAS pollution on aquatic ecosystems were investigated by evaluating a number of characteristics, including extracellular polymeric substances (EPSs) and chlorophyll content as well as the diversity of the microorganisms in the biofilms. Therefore, this review will provide crucial information on the possible adverse effects of PFASs on fish growth, reproduction, gut microbial dysbiosis, and its potential endocrine disruption. This information aims to help the researchers and academicians work and come up with possible remedial measures to protect aquatic ecosystems as future works need to be focus on techno-economic assessment, life cycle assessment, and multi criteria decision analysis systems that screen PFAS-containing samples. New innovative methods requires further development to reach detection at the permissible regulatory limits.

Assessment of mine post-closure strategies by integrating evidential reasoning and fuzzy cognitive maps: Toward sustainable mining policy

This study proposes a novel framework based on evidential reasoning and fuzzy cognitive map to evaluate post-closure strategies for open-pit mine reclamation, with a focus on sustainable mining. The framework enables a reasonable assessment of multiple strategies and criteria within a complex dynamic decision analysis system under uncertainty. This study introduces two novel aspects: linking the weight outputs of fuzzy cognitive maps to the evidential reasoning process and considering a broad range of criteria and reclamation strategies toward sustainable mining. This study considers various strategies, focusing on tailings, waste rocks, and demolition materials as filling materials to reclaim pits and reduce mine waste footprints. In evidential reasoning, causal weights were determined by a fuzzy cognitive map, which revealed that social criteria with a causal weight >0.96 were found the highest impact on cause-and-effect. The framework was applied to a large-scale mine with high discontinuities and acidity potentials, a local ecosystem with a high piezometric level, and low rainfall. A post-closure strategy using tailings as the main filling material was found most suitable, as it eliminates material transport and supply costs and reduces the adverse environmental effects and social complaints.

Selecting suitable sites for groundwater recharge in Jordan using the spreading techniques via the integration of multi-criteria decision analysis and geographic information system tools

Over exploitation of groundwater resources in Jordan has resulted in the depletion and degradation of many groundwater aquifers. Most aquifers are heavily exploited and are expected to dry up by 2040. These pressing challenges require Jordan to find creative and sustainable solutions. Since the annual natural groundwater recharge rate is limited to 0.1–5%, managed aquifer recharge is a proposed solution for Jordan to enhance recharge. The spreading technique is one method used to deliberately recharge water into groundwater aquifers for subsequent recovery or environmental benefits. This study presents a tool based on a geographic information system-multi criteria analysis to identify the potential sites for groundwater recharge in Jordan using the spreading technique. Large sets of spatial data were used to develop a potential site suitability map for managed aquifer recharge spreading methods; the criteria were chosen based on technical, economic, and environmental considerations. The site assessment combined fourteen thematic maps to create suitability maps using the weighted linear combination approach, which were combined with constraint mapping using the Boolean logic. Constraint mapping showed that nearly 47% (7198 km2) of the study area did not meet the minimum criteria. The site assessment criteria on the remaining areas showed that about 4% (618.7 km2) of the study area has low suitability, 14% (2123 km2) has moderate suitability, 20% (3101 km2) is suitable, and 15% (2388 km2) is highly suitable. Managed aquifer recharge has a great potential in the relief of water stress in arid areas. Existing geospatial tools and the increasing availability of spatial data are a great asset to local authorities in water planners.

Evaluation on power marketing decision evaluation based on Bayesian network

Abstract The daily production and life of human beings are inseparable from electricity. As the power supplier, electric power enterprises provide power demand for the majority of users. In the new era, electric power enterprises are also facing market-oriented reform. The focus of reform is electric power marketing. The formulation of electric power marketing strategy needs scientific decision-making analysis as guidance. With the increase of power demand, the scale of power grid is also expanding continuously. With the introduction of new energy equipment, the power system is becoming more and more complex, and it is difficult for relevant staff to effectively monitor and analyze the system. Combined with the above situation, this paper combined Bayesian network to build a power marketing decision analysis system, and combined Bayesian algorithm to test the power marketing real-time cost control system. The experimental results showed that the average judgment accuracy was 91.90 %, and the average warning time was 0.39 s. From the above data, it can be seen that this algorithm can play a good optimization effect on the performance of the system. In this paper, the elasticity test of the power system was also carried out from the aspect of wind speed, and the results showed that the maximum elasticity value can reach 0.94. It can be seen that the elasticity effect of the power system is good as a whole under different wind speeds.

EFFECT OF TYPES AND CONCENTRATIONS OF STABILIZERS ON THE CHARACTERISTICS OF EMPRIT GINGER (Zingiber officinale var. amarum) EXTRACT TEMPE BEVERAGE

In the making of emprit ginger extract tempe beverage requires the addition of a stabilizer to increase the stability and viscosity of the product and each stabilizer has a different effect from one another. This study aims to determine the characteristics of gum arabic stabilizer, Carboxymethyl Cellulose (CMC) and soy lecithin in emprit ginger extract tempe beverage used 0%, 0.3%, 0.5%, 0.7%, and 0.9% of each stabilizer. The observations were physical properties such as stability and viscosity and chemical analysis includes protein content, and pH value. This study used completely randomized design (CRD) with two factors (F1 is the type of stabilizer and F2 is the concentration of the stabilizer) and carried out with 3 replications. The obtained data was analyzed with ANOVA followed by Duncan's test. Decision system analysis was performed using the MADM-SAW method to obtain the best type and concentration of stabilizer. CMC was found out in the first rank of used stabilizers in 0.5% concentration with stability in 21%, viscosity was 2.17 poise, an ash content was 0.26%, protein content was 12.77%, and pH value was 6.2.

Spatial Analysis of the Suitability of Hass Avocado Cultivation in the Cauca Department, Colombia, Using Multi-Criteria Decision Analysis and Geographic Information Systems

Avocado is an important export and consumption product in Colombia, and its economic importance is expected to increase in the coming years. With its vast potential territory for avocado cultivation, the department of Cauca is a crucial area for producing this variety. However, small producers in the region often need more knowledge of the most suitable locations for planting. This study seeks to determine the ideal areas for Hass avocado cultivation in Cauca using geographic information tools and multi-criteria decision analysis, using a set of official data from different governmental entities and the hierarchical analytical process that allows determining the intensity of the interrelation of factors in the cultivation of Hass avocado. The results indicate that the municipalities near the Popayán plateau have the most significant potential for Hass avocado production, using the analytical hierarchy process. Approximately 9.2% of the administrative territory of the region is classified as highly suitable for Hass avocado cultivation, and an additional 14.2% is considered moderately suitable, constituting about 700,000 hectares of arable land. This research provides decision-makers and producers with valuable knowledge to support and improve Hass avocado agriculture in the region by implementing agricultural engineering practices.

The impact of knowledge management on the research capacity of university lecturers in Hanoi

This study was conducted with the objective of evaluating the influence of knowledge management on the research capacity of university lecturers in Hanoi. First, the decision system analysis method was used for the decision-making process of the knowledge management model through three rounds of interviews with 15 experts from universities, research institutes, and scientific journals. Five factors, namely knowledge creation, knowledge collection, knowledge sharing, knowledge application, and knowledge management with big data, were then identified. A survey was conducted with 388 participants, and the collected data were analyzed through partial least squares structural equation modeling. Accordingly, the knowledge management model with five factors that affect the motivation of research and the research capacity of lecturers at universities in Hanoi was evaluated, and the significant values of the reliability and suitability of the model were accepted, showing that the proposed model is suitable. The test results showed that knowledge creation, knowledge collection, knowledge sharing, and knowledge management with big data had a significant relationship with the faculty's research capacity. The analysis revealed that knowledge creation, knowledge application, and knowledge management with big data had a significant impact on the motivation of lecturers for research. The results also showed the direct impact of research motivation on lecturers' research capacity. Furthermore, the indirect relationships between knowledge creation, knowledge sharing, knowledge collection, and knowledge management with big data and research capacity through research motivation is a noteworthy finding of this study.

Human Resource Management Decision System University Based on Decision Model

The purpose of university personnel management is to improve the efficiency of running a school by optimizing the allocation of university human resources. Personnel management is one of the most important aspects of university administration, as it plays a key role in the formation of discipline teams and management teams. The use of advanced information technology is to improve the efficiency of personnel management, the establishment of university human resources analysis system, and to promote the school management work. Combining with the achievements of office automation and decision support development, this study analyzes the realization methods and key technologies of human resource management in university decision system, discusses the significance of human resource management in university decision system analysis based on decision model, and constructs human resource management in university decision system. This study first introduces the basic content of human resource management decision model and makes a comprehensive analysis of human resource demand prediction and then constructs a human resource management in university decision model according to the analysis structure. After defining the construction path of the decision‐making model of human resource management in colleges and universities, the human resource grading and promotion analysis is carried out to additionally define the prediction of human resource demand in universities. Finally, the decision system is realized and tested by means of mathematical model.

A Novel Framework for Analysis of Road Traffic Information for Decision Support by Using Data Mining Techniques

As we know we want traffic data analysis, data mining measures are recommended to help manage and traffic information decision making. Such as this limit, the road type is added intelligence analysis and decision support are another gave. This model has a data collection system and the data warehouse at its heart, and works well mathematical intelligence techniques and the invention of decision support system. As the main part of this report, the main parts of the model, the main process and an implementation plan is developed. An intelligent urban traffic decision analysis system is a system designed to solve open road problems, improve road safety and quality, and improve road quality work. The application of big data mining technology can improve various capabilities types of analysis and processing of traffic information, spread rapidly and provide a decision reference for the application of intelligent transport systems, which will be carried out to ensure smooth and safe roads. This topic will introduce the concept of large data mining technology and intelligent transport systems, and review the architecture of smart city road systems based on big data technology and design implementation of the mining process.

Identification of suitable sites for rainwater harvesting using GIS-based multi-criteria approach in Nusa Penida Island, Bali Province, Indonesia

The critical step in increasing water availability and land productivity in areas with freshwater scarcity, such as arid and semi-arid, is identifying suitable sites for Rain Water Harvesting (RWH). Identifying RWH suitable sites is site-specific due to a wide variety of a region’s characteristics. Biophysical (slope, soil texture, drainage density, land use), hydrological (runoff potential), and socio-economic (distance to road, distance to river, distance to settlement) parameters of the study area were implemented integrating multi-criteria decision analysis (analytical hierarchy processes) and Geographic Information System (GIS) to evaluate RWH suitable sites in Nusa Penida Island, Indonesia. This study’s parameters and hybrid method were effective tools for identifying RWH suitable sites. The result also indicated that approximately 38% of the Nusa Penida Island is highly suited for RWH. These areas are characterized by dryland farming as the dominant land use, gentle slope, high runoff potential, high drainage density, and moderately fine soil texture. The initial identification of RWH potential sites could be valuable information in completing water conservation programs for several purposes. This study’s approach also contributes to developing a suitable RWH identification methodology, especially for dry regions in Indonesia.