A Review on the Application of Natural Computing in Environmental Informatics

Natural computing offers new opportunities to understand, model and analyze the complexity of the physical and human-created environment. This paper examines the application of natural computing in environmental informatics, by investigating related work in this research field. Various nature-inspired techniques are presented, which have been employed to solve different relevant problems. Advantages and disadvantages of these techniques are discussed, together with analysis of how natural computing is generally used in environmental research.Comment: Proc. of EnviroInfo 201

Participatory Ecosystem Management Planning at Tuzla Lake (Turkey) Using Fuzzy Cognitive Mapping

A participatory environmental management plan was prepared for Tuzla Lake, Turkey. Fuzzy cognitive mapping approach was used to obtain stakeholder views and desires. Cognitive maps were prepared with 44 stakeholders (villagers, local decisionmakers, government and non-government organization (NGO) officials). Graph theory indices, statistical methods and "What-if" simulations were used in the analysis. The most mentioned variables were livelihood, agriculture and animal husbandry. The most central variable was agriculture for local people (villagers and local decisionmakers) and education for NGO & Government officials. All the stakeholders agreed that livelihood was increased by agriculture and animal husbandry while hunting decreased birds and wildlife. Although local people focused on their livelihoods, NGO & Government officials focused on conservation of Tuzla Lake and education of local people. Stakeholders indicated that the conservation status of Tuzla Lake should be strengthened to conserve the ecosystem and biodiversity, which may be negatively impacted by agriculture and irrigation. Stakeholders mentioned salt extraction, ecotourism, and carpet weaving as alternative economic activities. Cognitive mapping provided an effective tool for the inclusion of the stakeholders' views and ensured initial participation in environmental planning and policy making.Comment: 43 pages, 4 figure

Interactive Problem Structuring with ICZM Stakeholders

Integrated Coastal Zone Management (ICZM) is struggling with a lack of science-management integration. Many computer systems, usually known as “decision support systems”, have been developed with the intention to make scientific knowledge about complex systems more accessible for coastal managers. These tools, allowing a multi-disciplinary approach with multi-criteria analyses, are designed for well-defined, structured problems. However, in practice stakeholder consensus on the problem structure is usually lacking. Aim of this paper is to explore the practical opportunities for the new so-called Quasta approach to structure complex problems in a group setting. This approach is based on a combination of Cognitive Mapping and Qualitative Probabilistic Networks. It comprehends a new type of computer system which is quite simple and flexible as well. The tool is tested in two workshops in which various coastal management issues were discussed. Evaluations of these workshops show that (1) this system helps stakeholders to make them aware of causal relationships, (2) it is useful for a qualitative exploration of scenarios, (3) it identifies the quantitative knowledge gaps of the problem being discussed and (4) the threshold for non technicians to use this tool is quite low.Integrated Coastal Zone Management, Problem Structuring, Stakeholder Participation, Cognitive Mapping, Interactive Policy Making

Recommender Thermometer for Measuring the Preparedness for Flood Resilience Management

A range of various thermometers and similar scales are employed in different human and resilience management activities: Distress Thermometer, Panic Thermometer, Fear Thermometer, fire danger rating, hurricane scales, earthquake scales (Richter Magnitude Scale, Mercalli Scale), Anxiety Thermometer, Help Thermometer, Problem Thermometer, Emotion Thermometer, Depression Thermometer, the Torino scale (assessing asteroid/comet impact prediction), Excessive Heat Watch, etc. Extensive financing of the preparedness for flood resilience management with overheated full-scale resilience management might be compared to someone ill running a fever of 41°C. As the financial crisis hits and resilience management financing cools down it reminds a sick person whose body temperature is too low. The degree indicated by the Recommender Thermometer for Measuring the Preparedness for Flood Resilience Management with a scale between Tmin=34,0° and Tmax=42,0° shows either cool or overheated preparedness for flood resilience management. The formalized presentation of this research shows how changes in the micro, meso and macro environment of resilience management and the extent to which the goals pursued by various interested parties are met cause corresponding changes in the “temperature” of the preparedness for resilience management. Global innovative aspects of the Recommender Thermometer developed by the authors of this paper are, primarily, its capacity to measure the “temperature” of the preparedness for flood resilience management automatically, to compile multiple alternative recommendations (preparedness for floods, including preparing your home for floods, taking precautions against a threat of floods, retrofitting for flood-prone areas, checking your house insurance; preparedness for bushfires, preparedness for cyclones, preparedness for severe storms, preparedness for heat waves, etc.) customised for a specific user, to perform multiple criteria analysis of the recommendations, and to select the ten most rational ones for that user. Across the world, no other system offers these functions yet. The Recommender Thermometer was developed and fine-tuned in the course of the Android (Academic Network for Disaster Resilience to Optimise educational Development) project

A STOCHASTIC SIMULATION-BASED HYBRID INTERVAL FUZZY PROGRAMMING APPROACH FOR OPTIMIZING THE TREATMENT OF RECOVERED OILY WATER

In this paper, a stochastic simulation-based hybrid interval fuzzy programming (SHIFP) approach is developed to aid the decision-making process by solving fuzzy linear optimization problems. Fuzzy set theory, probability theory, and interval analysis are integrated to take into account the effect of imprecise information, subjective judgment, and variable environmental conditions. A case study related to oily water treatment during offshore oil spill clean-up operations is conducted to demonstrate the applicability of the proposed approach. The results suggest that producing a random sequence of triangular fuzzy numbers in a given interval is equivalent to a normal distribution when using the centroid defuzzification method. It also shows that the defuzzified optimal solutions follow the normal distribution and range from 3,000-3,700 tons, given the budget constraint (CAD 110,000-150,000). The normality seems to be able to propagate throughout the optimization process, yet this interesting finding deserves more in-depth study and needs more rigorous mathematical proof to validate its applicability and feasibility. In addition, the optimal decision variables can be categorized into several groups with different probability such that decision makers can wisely allocate limited resources with higher confidence in a short period of time. This study is expected to advise the industries and authorities on how to distribute resources and maximize the treatment efficiency of oily water in a short period of time, particularly in the context of harsh environments

A review on the integration of artificial intelligence into coastal modeling

Author name used in this publication: Kwokwing Chau2005-2006 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Modeling nature-based and cultural recreation preferences in mediterranean regions as opportunities for smart tourism and diversification

The tourism and recreational o er of Mediterranean destinations involves, essentially, the promotion of mass tourism, based on the appeal of the sun and beach, and the quality of its coastal assets. Alongside the impacts of climate change, poor tourism diversification represents a threat to the resilience of the territory. Thus, heterogenization of noncoastal tourism products presents an opportunity to strengthen regional resilience to present and future challenges, hence the need to study, comparatively, the complementary preferences of tourists and residents of these regions in order to unveil their willingness to diversify their recreational experience, not only in coastal spaces, but also—and especially—in interior territories with low urban density. Consequently, this strategic option may represent a way of strengthening resilience and sustainability through diversification. In this context, a survey was conducted among 400 beach tourists and 400 residents of a case study—namely, three municipalities of the Algarve region in southern Portugal—in order to analyze their degree of preference for activities besides the sun and beach, such as nature-based and cultural tourism activities, and to probe the enhancement potential of each tourism and recreational activity through the various landscape units considered by experts, stakeholders, and tour operators. The respective degree of preference and enhancement potential were indexed to the area of each landscape unit. Subsequently, respecting the existing recreational structure and constraints, a suitability map for territory enhancement and the implementation of smart tourism practices for each tourism activity and landscape unit is presented. Results show a significant preference for noncoastal outdoor recreational activities.FCT- Fundação para a Ciência e Tecnologia: SFRH/BD/102328/2014; PTDC/GES-URB/31928/2017info:eu-repo/semantics/publishedVersio

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested