Land-use suitability evaluation for organic rice cultivation using fuzzy-AHP ELECTRE method

Land conversion to organic agriculture is the answer to land degradation problems that interfere with land resources sustainability. An evaluation of land-use suitability is crucial to measure the appropriateness of land for agricultural cultivation. Specifically, organic rice cultivation has some particular standard criteria such as temperature, rainfall, soil depth, pH, c-organic, slope, erosion level, a transition period that influence ranking results, and land suitability classes. Eight organic farmlands were used as alternatives, namely Sawangan, Mangunsari, Tirtosari, Podosoko, Butuh, Krogowanan, Kapuhan, and Jati. Fuzzy Analytic Hierarchy process is used to determine the level of importance of the criteria based on weight assessments by three agricultural experts. The ELECTRE method is applied to rank the most suitable land from several alternatives for organic rice cultivation. The combination of these two multi-criteria decision-making methods complements each other to solve problems in land suitability evaluation. A web-based decision support system (DSS) was created to accelerate data processing integration and present factual information from the land suitability selection process. The implementation of DSS with fuzzy-AHP ELECTRE for evaluating land-use suitability in organic rice cultivation provided the best score for Tirtosari with Ekl=4 and spearman rank correlation the system comparison results with actual data rs=0.95. This study's results indicate that integrating the web with fuzzy-AHP ELECTRE is quite effectively applied for decision-making in organic farming

Land-use suitability evaluation for organic rice cultivation using fuzzy-AHP ELECTRE method

Land conversion to organic agriculture is the answer to land degradation problems that interfere with land resources sustainability. An evaluation of land-use suitability is crucial to measure the appropriateness of land for agricultural cultivation. Specifically, organic rice cultivation has some particular standard criteria such as temperature, rainfall, soil depth, pH, c-organic, slope, erosion level, a transition period that influence ranking results, and land suitability classes. Eight organic farmlands were used as alternatives, namely Sawangan, Mangunsari, Tirtosari, Podosoko, Butuh, Krogowanan, Kapuhan, and Jati. Fuzzy Analytic Hierarchy process is used to determine the level of importance of the criteria based on weight assessments by three agricultural experts. The ELECTRE method is applied to rank the most suitable land from several alternatives for organic rice cultivation. The combination of these two multi-criteria decision-making methods complements each other to solve problems in land suitability evaluation. A web-based decision support system (DSS) was created to accelerate data processing integration and present factual information from the land suitability selection process. The implementation of DSS with fuzzy-AHP ELECTRE for evaluating land-use suitability in organic rice cultivation provided the best score for Tirtosari with Ekl=4 and spearman rank correlation the system comparison results with actual data rs=0.95. This study's results indicate that integrating the web with fuzzy-AHP ELECTRE is quite effectively applied for decision-making in organic farming

Intelligent Decision Support System for Energy Management in Demand Response Programs and Residential and Industrial Sectors of the Smart Grid

This PhD thesis addresses the complexity of the energy efficiency control problem in residential and industrial customers of Smart electrical Grid, and examines the main factors that affect energy demand, and proposes an intelligent decision support system for applications of demand response. A multi criteria decision making algorithm is combined with a combinatorial optimization technique to assist energy managers to decide whether to participate in demand response programs or obtain energy from distributed energy resources

APPLICATION OF RECLAIMED WASTEWATER FOR AGRICULTURAL IRRIGATION: DEVELOPING A DECISION SUPPORT TOOL USING SPATIAL MULTI-CRITERIA DECISION ANALYSIS

Intensified climate variability, depleting groundwater, and escalating water demand create severe stress on high-quality freshwater sources used for agricultural irrigation. These challenges necessitate the exploration of alternative water sources such as reclaimed water to reduce the pressure on freshwater sources. To do so, it is key to investigate the spatial pattern of areas that are more suitable for water reuse to determine the potential of reclaimed wastewater use for irrigation. This study provides a systematic decision-analysis framework for the decision-makers using an integrated process-based hydrologic model for sustainable agricultural water management. The outcomes of this study provide evidence of the feasibility of reclaimed wastewater use in the agricultural sector. The two objectives of this study were to: 1) identify the locations that are most suitable for the reclaimed wastewater use in agriculture (hotspots); and 2) develop the watershed-scale models to assess the agricultural water budget and crop production using different water conservation scenarios including reclaimed wastewater use. To achieve the first objective, a decision-making framework was developed by using the Geographic Information System and Multi-Criteria Decision Analysis (GIS-MCDA). This framework was then tested in the Southwest (California), and the Mid-Atlantic (Maryland) regions. Based on WWTPs’ proximity, sufficient water availability, and appropriate treatment process of the treated wastewater, the “Most Suitable” and “Moderately Suitable” agricultural areas were found to be approximately 145.5 km2, and 276 km2 for California and, 26.4 km2 and 798.8 km2 for Maryland, respectively. These results were then used to develop the hydrologic models to examine water conservation and water reuse scenarios under real-world conditions, using the Soil and Water Assessment Tool (SWAT). In California, the combination of auto irrigation (AI) and regulated deficit irrigation (RDI) resulted in higher WP for both almond and grape (> 0.50 kg/m3). Results also suggested that the wastewater reuse in almond and grape irrigation could reduce groundwater consumption more than 74% and 90% under RDI and AI scenarios, respectively. For Maryland, model simulations suggested that the green water productivity (only rainfall) can be improved up to 0.713 kg/m3 for corn and 0.37 kg/m3 for soybean under the reclaimed wastewater use scenario

State-of-the-Art Report on Systems Analysis Methods for Resolution of Conflicts in Water Resources Management

Water is an important factor in conflicts among stakeholders at the local, regional, and even international level. Water conflicts have taken many forms, but they almost always arise from the fact that the freshwater resources of the world are not partitioned to match the political borders, nor are they evenly distributed in space and time. Two or more countries share the watersheds of 261 major rivers and nearly half of the land area of the wo rld is in international river basins. Water has been used as a military and political goal. Water has been a weapon of war. Water systems have been targets during the war. A role of systems approach has been investigated in this report as an approach for resolution of conflicts over water. A review of systems approach provides some basic knowledge of tools and techniques as they apply to water management and conflict resolution. Report provides a classification and description of water conflicts by addressing issues of scale, integrated water management and the role of stakeholders. Four large-scale examples are selected to illustrate the application of systems approach to water conflicts: (a) hydropower development in Canada; (b) multipurpose use of Danube river in Europe; (c) international water conflict between USA and Canada; and (d) Aral See in Asia. Water conflict resolution process involves various sources of uncertainty. One section of the report provides some examples of systems tools that can be used to address objective and subjective uncertainties with special emphasis on the utility of the fuzzy set theory. Systems analysis is known to be driven by the development of computer technology. Last section of the report provides one view of the future and systems tools that will be used for water resources management. Role of the virtual databases, computer and communication networks is investigated in the context of water conflicts and their resolution.https://ir.lib.uwo.ca/wrrr/1005/thumbnail.jp

Incident Prioritisation for Intrusion Response Systems

The landscape of security threats continues to evolve, with attacks becoming more serious and the number of vulnerabilities rising. To manage these threats, many security studies have been undertaken in recent years, mainly focusing on improving detection, prevention and response efficiency. Although there are security tools such as antivirus software and firewalls available to counter them, Intrusion Detection Systems and similar tools such as Intrusion Prevention Systems are still one of the most popular approaches. There are hundreds of published works related to intrusion detection that aim to increase the efficiency and reliability of detection, prevention and response systems. Whilst intrusion detection system technologies have advanced, there are still areas available to explore, particularly with respect to the process of selecting appropriate responses. Supporting a variety of response options, such as proactive, reactive and passive responses, enables security analysts to select the most appropriate response in different contexts. In view of that, a methodical approach that identifies important incidents as opposed to trivial ones is first needed. However, with thousands of incidents identified every day, relying upon manual processes to identify their importance and urgency is complicated, difficult, error-prone and time-consuming, and so prioritising them automatically would help security analysts to focus only on the most critical ones. The existing approaches to incident prioritisation provide various ways to prioritise incidents, but less attention has been given to adopting them into an automated response system. Although some studies have realised the advantages of prioritisation, they released no further studies showing they had continued to investigate the effectiveness of the process. This study concerns enhancing the incident prioritisation scheme to identify critical incidents based upon their criticality and urgency, in order to facilitate an autonomous mode for the response selection process in Intrusion Response Systems. To achieve this aim, this study proposed a novel framework which combines models and strategies identified from the comprehensive literature review. A model to estimate the level of risks of incidents is established, named the Risk Index Model (RIM). With different levels of risk, the Response Strategy Model (RSM) dynamically maps incidents into different types of response, with serious incidents being mapped to active responses in order to minimise their impact, while incidents with less impact have passive responses. The combination of these models provides a seamless way to map incidents automatically; however, it needs to be evaluated in terms of its effectiveness and performances. To demonstrate the results, an evaluation study with four stages was undertaken; these stages were a feasibility study of the RIM, comparison studies with industrial standards such as Common Vulnerabilities Scoring System (CVSS) and Snort, an examination of the effect of different strategies in the rating and ranking process, and a test of the effectiveness and performance of the Response Strategy Model (RSM). With promising results being gathered, a proof-of-concept study was conducted to demonstrate the framework using a live traffic network simulation with online assessment mode via the Security Incident Prioritisation Module (SIPM); this study was used to investigate its effectiveness and practicality. Through the results gathered, this study has demonstrated that the prioritisation process can feasibly be used to facilitate the response selection process in Intrusion Response Systems. The main contribution of this study is to have proposed, designed, evaluated and simulated a framework to support the incident prioritisation process for Intrusion Response Systems.Ministry of Higher Education in Malaysia and University of Malay

Enhancing Evacuation Planning in Public Buildings: Optimising Egress Location and Protection

Effective evacuation strategies are crucial for ensuring the safety of individuals during emergencies and disasters. Despite significant progress in evacuation planning, the intricate dynamics of disaster scenarios and uncertainties inherent in such situations need to be better incorporated in planning egress locations to enhance safety in buildings. This work focuses on strategically locating egress points within public buildings, acknowledging their pivotal role in facilitating secure evacuations. Optimising egress points improves evacuation efficiency and minimises associated risks, significantly improving evacuation. This research introduces an innovative approach that integrates optimisation models, addresses decision-making complexities, explores practical applications, and considers potential attack scenarios. The study explores evacuation dynamics across diverse scenarios, elevating preparedness, and safety protocols to protect public assets and lives. Developing mixedinteger programming models establishes a foundation for optimising egress locations. MCDM is then employed, leveraging the F-AHP to address uncertainties in egress selection. Practicality is realised through integrating Revit and AnyLogic software, facilitating assessment through BIM and ABM. A stochastic BP model is formulated, addressing both Defender and Attacker perspectives for enhanced egress strategies. This model strategically allocates resources to fortify egresses, ensuring occupant safety during evacuations. Contributions further optimisation approaches, fortification strategies, and progressive enhancements in evacuation planning. These collectively address key challenges and gaps in existing literature, enhancing evacuation efficiency and public safety during emergencies. The research bridges gaps in existing approaches, providing a framework for future investigations into optimising evacuation strategies, enhanced disaster preparation, and further advancements in the field

Natural hazards in electricity grids: from landscape dynamics to optimal mitigation and adaptation approaches

This article discusses the increasing significance of microgrids in fortifying electricity grid resilience amidst evolving global energy trends. The study employs the Multi-Criteria Decision-Making Analytic Hierarchy Process (MCDM-AHP) to assess strategies for mitigating and adapting to natural hazards, utilizing a purposeful and structured judgment process with pairwise comparisons and eigenvalue calculations to establish overall preference scores. The chosen methodology, MCDM-AHP, is highlighted for its effectiveness in handling complex, multidimensional decision-making challenges with interrelated criteria and dependencies, guided by subjective expert judgment. The analysis of relative weights underscores the utmost importance of effectiveness, resilience enhancement, and risk reduction while also highlighting the significance of technological maturity, scalability, flexibility, long-term sustainability, integration with other strategies, community engagement, resource availability, cost-effectiveness, ease of implementation, education and training, environmental impact, and regulatory and policy compliance in evaluating strategies for natural hazard mitigation and adaptation. 'Distributed Generation' emerges as the top-performing option, followed closely by 'Demand Response' and 'Artificial Intelligence', while 'Scenario Planning', 'Hardening Infrastructure', 'Collaboration', and 'Regular Maintenance' also demonstrate varying levels of effectiveness across evaluated criteria in the mitigation and adaptation of natural hazards. This research investigates the varied responses of electricity grid landscapes to natural hazards, utilizing MCDM-AHP to assess resilience strategies, providing insights into the strengths and weaknesses of different grid types, and offering a comprehensive framework for policymakers and practitioners to enhance energy system resilience and reliability