69 research outputs found
ΠΠ»ΠΈΡΠ½ΠΈΠ΅ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ Π³Π°Π΄ΠΎΠ»ΠΈΠ½ΠΈΠΉ ΡΠΎΠ΄Π΅ΡΠΆΠ°ΡΠΈΡ ΡΠ²ΡΠ»ΠΎΠ² ΡΠ΅Π°ΠΊΡΠΎΡΠ° ΠΠΠΠ -1000 Π½Π° Π²ΡΠ³ΠΎΡΠ°Π½ΠΈΠ΅
Π Π°Π·Π»ΠΈΡΠ½ΡΠΉ ΡΠΎΡΡΠ°Π² ΠΈ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΠΎΠ΅ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ Π²ΡΠ³ΠΎΡΠ°ΡΡΠΈΡ
ΠΏΠΎΠ³Π»ΠΎΡΠΈΡΠ΅Π»Π΅ΠΉ ΠΏΠΎ-ΡΠ°Π·Π½ΠΎΠΌΡ Π²Π»ΠΈΡΡΡ Π½Π° ΡΠ°Π·ΠΌΠ½ΠΎΠΆΠ°ΡΡΠΈΠ΅ ΠΈ ΡΠ΅ΠΏΠ»ΠΎΡΠΈΠ·ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΠ²ΠΎΠΉΡΡΠ²Π° ΡΠ΅Π°ΠΊΡΠΎΡΠ°. Π ΡΠ°Π±ΠΎΡΠ΅ ΡΠΎΠ·Π΄Π°Π½Π° ΡΠ°ΡΡΠ΅ΡΠ½Π°Ρ 3D ΠΌΠΎΠ΄Π΅Π»Ρ Π’ΠΠ‘ ΡΠ΅Π°ΠΊΡΠΎΡΠ° Ρ Π²ΡΠ³ΠΎΡΠ°ΡΡΠΈΠΌΠΈ ΠΏΠΎΠ³Π»ΠΎΡΠΈΡΠ΅Π»ΡΠΌΠΈ. Π ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅ Π²ΡΠ³ΠΎΡΠ°ΡΡΠΈΡ
ΠΏΠΎΠ³Π»ΠΎΡΠΈΡΠ΅Π»Π΅ΠΉ ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡΡΡΡ ΡΡΠ°Π΄ΠΈΡΠΈΠΎΠ½Π½ΠΎ-ΠΏΡΠΈΠΌΠ΅Π½ΡΠ΅ΠΌΡΠ΅ Gd2O3-ΡΠΎΠ΄Π΅ΡΠΆΠ°ΡΠΈΠ΅ ΡΠ²ΡΠ»Ρ ΠΈ ΡΠ²ΡΠ»Ρ Ρ AmO2. ΠΡΠΎΠ²Π΅Π΄Π΅Π½Π½ΡΠ΅ ΡΠ°ΡΡΠ΅ΡΡ ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΡ Π½Π΅ΠΉΡΡΠΎΠ½Π½ΠΎ-ΡΠΈΠ·ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΡΠ²ΠΎΠΉΡΡΠ²Π° ΡΠ΅Π°ΠΊΡΠΎΡΠ° ΠΈ Π½ΠΈΠ²Π΅Π»ΠΈΡΠΎΠ²Π°ΡΡ, Π²ΠΎΠ·Π½ΠΈΠΊΠ°ΡΡΠΈΠ΅ ΠΎΡΡΠ΅ΡΡ ΡΠ½Π΅ΡΠ³ΠΎΠ²ΡΠ΄Π΅Π»Π΅Π½ΠΈΡ Π² ΠΏΠ΅ΡΠ΅Ρ
ΠΎΠ΄Π½ΡΡ
ΡΠ΅ΠΆΠΈΠΌΠ°Ρ
ΡΠΊΡΠΏΠ»ΡΠ°ΡΠ°ΡΠΈΠΈ
ΠΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΡΠ²Π΅ΡΠ΄ΠΎΡΠ°Π·Π½ΠΎΠ³ΠΎ ΠΊΠ°ΡΠ°Π»ΠΈΠ·Π°ΡΠΎΡΠ° Π΄Π»Ρ Π²ΡΠ΄Π΅Π»Π΅Π½ΠΈΡ ΠΏΠ°Π»Π»Π°Π΄ΠΈΡ ΠΈΠ· ΠΏΡΠΎΠ΄ΡΠΊΡΠΎΠ² ΡΠ°Π΄ΠΈΠΎΡ ΠΈΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΏΠ΅ΡΠ΅ΡΠ°Π±ΠΎΡΠΊΠΈ ΠΠ―Π’
Fuzzy Indicators for Interdisciplinary Performance Assessment of Water Resources Management
NeuroFuzzy modelling for conflict resolution in irrigation management
Management of large-scale irrigation schemes is more complicated than commonly recognized. Irrigation management involves complicated social, organizational, legal, and economical issues in addition to the undoubtedly important technical matters and environmental aspects. Management decisions have potential to be controversial because the involved groups (irrigation officials and water users) hold distinct interests and conflicting objectives. Irrigation plans, bureaucratically decided by irrigation officials, are often rejected by water users causing additional conflicts in managing the system and adversely affecting the schemes' sustainability. It is believed that involving water user associations at different stages of management is a key mechanism towards the improvement of irrigation systems. Therefore, participatory management of irrigation systems has long been an objective for many authorities. However, little has been done to support participation of both groups. In response to this issue, the current work is devoted to introduce a framework for participatory planning of seasonal management decisions and to propose a model, which enables assessment of planning alternatives. Based on a detailed system analysis, the elements of the planning decisions (alternatives, restrictions, and objectives) are identified, and in turn, a set of performance indicators are defined to quantify the conflicting objectives of the groups involved. The proposed framework suggests a committee consisting of scheme managers and farmers. The committee is responsible for defining planning alternatives, simulating them, and assessing their economical, technical, social, and environmental performance. The assessment involves conflicting indicators with a high level of uncertainty and noncommensurability as well as competing interests and vague viewpoints of involved decision makers (DMs). Consequently, the situation is formulated mathematically as a Fuzzy-Multiple-Participant- Multiple-Criteria Decision Making Problem. A three-level hierarchical structure is adopted to formulate the interrelationship of the indicators and to aggregate them in order to obtain a single value that reflects the overall performance of each suggested plan. An assessment model is developed using a combination of both Artificial Neural Networks (ANNs) and Fuzzy Logic (FL) to build a so-called NeuroFuzzy Assessment Model (NFAM). The NFAM utilizes the architecture of ANNs to represent the suggested hierarchical structure of indicators. The learning capability of the ANNs is employed to capture the conflicting assessment opinions of DMs. An Analytic Hierarchy Process (AHP) is applied to weight the involved DMs with respect to their experience and qualification. The weights are taken into consideration when training sets are formulated for tuning the model. FL is used to handle the uncertainty, vagueness, and the non- commensurability related to the aggregation of the indicators within a strict mathematical framework. Finally, a numerical example is performed to demonstrate the feasibility of the proposed NFAM. The framework is considered to be an important contribution towards resolving conflicts in irrigation management, since it identifies both roles of participants and rules for their participation. The developed NFAM is an intelligent, simple and flexible tool to assess planning alternatives. The current work encourages researchers to utilize the NeuroFuzzy technology in order to enhance modeling of water resources problems, especially in ecohydrological modeling
Fuzzy Indicators for Interdisciplinary Performance Assessment of Water Resources Management
Education for Sustainable Development Toolkit : ESD Kit for teachers, educators and curriculum developers : LEVEL 3
Education for Sustainable Development Toolkit : ESD kit for teachers, educators and curriculum developers : LEVEL 1
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