8,183 research outputs found

    Sustainability ranking of desalination plants using Mamdani Fuzzy Logic Inference Systems

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    As water desalination continues to expand globally, desalination plants are continually under pressure to meet the requirements of sustainable development. However, the majority of desalination sustainability research has focused on new desalination projects, with limited research on sustainability performance of existing desalination plants. This is particularly important while considering countries with limited resources for freshwater such as the United Arab Emirates (UAE) as it is heavily reliant on existing desalination infrastructure. In this regard, the current research deals with the sustainability analysis of desalination processes using a generic sustainability ranking framework based on Mamdani Fuzzy Logic Inference Systems. The fuzzy-based models were validated using data from two typical desalination plants in the UAE. The promising results obtained from the fuzzy ranking framework suggest this more in-depth sustainability analysis should be beneficial due to its flexibility and adaptability in meeting the requirements of desalination sustainability

    River Ecological Restoration and Groundwater Artificial Recharge

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    Three of the eleven papers focused on groundwater recharge and its impacts on the groundwater regime, in which recharge was caused by riverbed leakage from river ecological restoration (artificial water replenishment). The issues of the hydrogeological parameters involved (such as the influence radius) were also reconsidered. Six papers focused on the impact of river ecological replenishment and other human activities on river and watershed ecology, and on groundwater quality and use function. The issues of ecological security at the watershed scale and deterioration of groundwater quality were of particular concern. Two papers focused on water resources carrying capacity and water resources reallocation at the regional scale, in the context of the fact that ecological water demand has been a significant topic of concern. The use of unconventional water resources such as brackish water has been emphasized in the research in this issue

    A Review on the Application of Natural Computing in Environmental Informatics

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    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

    Locating Water Desalination Facilities for Municipal Drinking Water Based on Qualitative and Quantitative Characteristics of Groundwater in Iran's Desert Regions

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    Groundwater resources have become the main resources for water supply due to the unavailability of surface water in arid zones. Arid zone's damage to groundwater resources will have a high impact on human life in arid zones comparing to other regions. Due to the lack of surface water resources in these arid zones, groundwater is used as a resource for drinking and sanitation purposes due to the lack of surface water resources in these arid zones. Water desalination facilities are set up in locations where there is both sufficient amount of water (quantitative criteria) and the extracted water has adequate quality (qualitative criteria). Therefore, an optimization model should be used to locate optimal places for water desalination facilities. Multi-criteria decision-making models are mathematical techniques that, by using the geographic information system, are able to evaluate the options under complicated and indefinite geographic conditions. This research prepares information and factor maps to assign weights to qualitative water maps which were combined in the form of an inductive network. Therefore, by employing the concept of fuzzy fusion models, this article presents a method for solving multi-criteria geographically-indeterminate problems, and finally finds an appropriate location for the construction of a water desalination system in the desert region of Birjand in Iran

    Management of Pollution in Groundwater Systems Using Neuro-Fuzzy Model

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    Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

    AI and OR in management of operations: history and trends

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    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

    Novel Hybrid Integration Approach of Bagging-Based Fisher’s Linear Discriminant Function for Groundwater Potential Analysis

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    © 2019, International Association for Mathematical Geosciences. Groundwater is a vital water source in the rural and urban areas of developing and developed nations. In this study, a novel hybrid integration approach of Fisher’s linear discriminant function (FLDA) with rotation forest (RFLDA) and bagging (BFLDA) ensembles was used for groundwater potential assessment at the Ningtiaota area in Shaanxi, China. A spatial database with 66 groundwater spring locations and 14 groundwater spring contributing factors was prepared; these factors were elevation, aspect, slope, plan and profile curvatures, sediment transport index, stream power index, topographic wetness index, distance to roads and streams, land use, lithology, soil and normalized difference vegetation index. The classifier attribute evaluation method based on the FLDA model was implemented to test the predictive competence of the mentioned contributing factors. The area under curve, confidence interval at 95%, standard error, Friedman test and Wilcoxon signed-rank test were used to compare and validate the success and prediction competence of the three applied models. According to the achieved results, the BFLDA model showed the most prediction competence, followed by the RFLDA and FLDA models, respectively. The resulting groundwater spring potential maps can be used for groundwater development plans and land use planning

    Advances in Study on Water Resources Carrying Capacity in China

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    AbstractThe article systematically reviews the history of water resource carrying capacity and shows that water resource carrying capacity through three exhibition stages: initial, prosperity and development. The initial stage of the study is concentrated on environmental vulnerability arid area of northwest, and put forward the concept of water resource carrying capacity. it focus on the research of the theory, quantitative research is only initial. In this phase, the writer mainly uses two methods, which are trend in conventional and fuzzy comprehensive evaluation, to study. The prosperous phase of the study extends to urban areas, drainage basin, etc. In this stage, the research mainly probes into water resource carrying capacity from characteristic, connotation and the index system, which are using a variety of new mathematical models, in order to let the study gradually transmute into quantitative-rization. The expansion phase of the study refers to groundwater resources carrying capacity, the areas of Karst and irrigation .In this stage, theory study has been especially mature, there are the artificial neural network mode and projection trace appraises model besides the first two stages methods in quantitative-rization evaluation. In the future, the study of water resources bearing capacity will be combined with water resource optional distribution and ecological water requirement enhance study representative area, simultaneously, paying more attention to the issue of recycling Reclaimed Water; During the study, quantitative analysis should be combined with advanced means such as remote sensing, etc. which can realize the development of study from static to dynamics

    Determine of Surface Water Quality Index in Iran

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    In modeling complex of environmental problems, researchers often fail to define precise statements about input and outcomes of contaminants, but fuzzy logic could help to dominate this logical indecision. The goal of this work is to propose a new river water quality indicator using fuzzy logic. The proposed index combines six indicators, and not only does it exhibit a tool that accounts for the discrepancy between the two base indices, but also provides a quantifiable score for the determined water quality. These classifications with a membership grade can be of a sound support for decision-making, and can help assign each section of a river a gradual quality sub-objective to be reached. To show the applicability of the proposed approach, the new indicator was used to classify water quality in a number of stations along the basins of Qarah-chai and Siminehrood. The obtained classifications were then compared to the conventional physicochemical water quality indicator currently in use in Iran. The results revealed that the fuzzy indicator provided stringent classifications compared to the conventional index in 38% and 44% of the cases for the two basins respectively. These noted exceptions are mainly due to the big disagreement between the different quality thresholds in the two standards, especially for fecal coliform and total phosphorus. These large disparities put forward an argument for the Iranian water quality law to be upgraded. Keywords: Fuzzy logic; Qarah-chai basin; Siminehrood; Water quality inde

    Groundwater quality for irrigation in an arid region-application of fuzzy logic techniques

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    Groundwater is the main source to answer the irrigation supply in several arid and semi-arid areas. In the present work, groundwater quality for irrigation purposes in the arid region of Menzel Habib (Tunisia) for thirty-six groundwater samples is assessed considering the application of different conventional water quality indicators, particularly, electrical conductivity (EC), sodium absorption ratio (SAR), soluble sodium percentage (SSP), magnesium adsorption ratio (MAR), Kelly ratio (KR), and permeability index (PI). The results obtained indicate a variability for EC: 3.06 to 14.98 mS.cm-1; SAR: 4.08 to 19.30; SSP: 35.78 to 71.53%; MAR: 34.19 to 56.01; PI: 38.47 to 72.74; and KR: 0.56 to 2.47. These results suggest that groundwater from Menzel Habib aquifer system is classified between excellent to unsuitable according to the applied water quality indices. Furthermore, the groundwater samples are also plotted in the Richards diagram classification system, based on the relation between SAR and EC, suggesting that almost groundwater samples present a harmful quality. Moreover, fuzzy logic model has been proposed and created to assess groundwater quality for irrigation. The membership functions are constructed for six significant parameters such as EC, SAR, SSP, MAR, KR, and PI and the rules are, then, fired to get a simple Fuzzy Irrigation Water Quality Index (FIWQI). The obtained groundwater quality results suggest that 3% of the samples from Menzel Habib region are considered as "good" for irrigation, 3% are classified as "good to permissible", 33% with a "permissible" quality, 36% "permissible to unsuitable", while 25% of groundwater present an "unsuitable" quality. Thus, the use of fuzzy logic techniques has more reliable and robust results by overcoming the uncertainties in the decision-making attributed to the conventional methods by the creation of new classes (excellent to good, good to permissible, and permissible to unsuitable) in addition to the classes proposed by Richards diagram classification (excellent, good, permissible, and unsuitable) to assess the groundwater quality suitability for irrigation purposes.This research was developed under the FCT–Fundação para a Ciência e a Tecnologia, I.P. program, through the project’s reference UIDB/04683/2020 and UIDP/04683/2020
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