Group Decision-Making Support for Sustainable Governance of Algal Bloom in Urban Lakes
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Summary
The comparison and discussion show that the group decision-making method is feasible and effective and can assist the sustainable management of algal bloom.
- Type
- article
- Published
- 2020-02-17
- Cited by
- 13
- References
- 47
- Access
- Open access
- OpenAlex
- https://openalex.org/W3005821173
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:213540369
Keywords
Beijing, Corporate governance, Algal bloom, Process (computing), Rank (graph theory)
References
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- Logistic Regression, AdaBoost and Bregman Distances
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- Support vector machines
- A Brief Introduction to Monte Carlo Simulation
- Artificial mixing to control cyanobacterial blooms: a review
- Some harmonic Aggregation Operators with 2-Tuple Linguistic Assessment Information and their Application to Multiple Attribute Group Decision Making
- A design framework for hierarchical ensemble of multiple feature extractors and multiple classifiers
- A linguistic mobile Decision Support System based on fuzzy ontology to facilitate knowledge mobilization
- Researches of Water Bloom Emergency Management Decision- making Method and System Based on Fuzzy Multiple Attribute Decision Making
- Correlation between Chlorophyll a and Algal Density of Surface Water in Urban of Beijing
- A Novel Group Decision-Making Method Based on Sensor Data and Fuzzy Information
- Expert Decision Support Technique for Algal Bloom Governance in Urban Lakes Based on Text Analysis
- Microorganisms-based methods for harmful algal blooms control: A review.
- A HYBRID FUZZY AHP-MABAC MODEL: APPLICATION IN THE SERBIAN ARMY – THE SELECTION OF THE LOCATION FOR DEEP WADING AS A TECHNIQUE OF CROSSING THE RIVER BY TANKS
- Semantic and Dweller-Based Decision Support System for the Reconfiguration of Domestic Environments: RecAAL
- An approach of improved Multivariate Timing-Random Deep Belief Net modelling for algal bloom prediction
- An approach of recursive timing deep belief network for algal bloom forecasting
- Indoor Tracking by RFID Fusion with IMU Data
Cited by
- Hybrid Deep Learning Predictor for Smart Agriculture Sensing Based on Empirical Mode Decomposition and Gated Recurrent Unit Group Model
- Fuzzy Boost Classifier of Decision Experts for Multicriteria Group Decision-Making
- A Biobjective Optimization Model for Expert Opinions Aggregation and Its Application in Group Decision Making
- A Machine Learning Approach for Estimating the Trophic State of Urban Waters Based on Remote Sensing and Environmental Factors
- Deep Prediction Model Based on Dual Decomposition with Entropy and Frequency Statistics for Nonstationary Time Series
- Modelling Phytoplankton Behaviour in the North and Irish Sea with Transformer Networks
- Retrieving Eutrophic Water in Highly Urbanized Area Coupling UAV Multispectral Data and Machine Learning Algorithms
- Deep Fusion Prediction Method for Nonstationary Time Series Based on Feature Augmentation and Extraction
- Artificial intelligence enabled participatory planning: a review
- Automatic Group Decision-Making for Algal Bloom Management Based on Information Self-Learning
- Automatic Decision-Making Method for River and Lake Pollution Control Based on Case and Domain Knowledge
- Multimodal Approach to Early Detection of Harmful Algal Blooms
- Microservices Infrastructure Architecture for the Cloud-Based Multi-Agent Group Decision Support Systems for Autonomous Cyberphysical Systems
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