King et al., 2016 - Google Patents
Combining ecohydrologic and transition probability-based modeling to simulate vegetation dynamics in a semi-arid rangelandKing et al., 2016
View PDF- Document ID
- 1674728582514011760
- Author
- King E
- Franz T
- Publication year
- Publication venue
- Ecological Modelling
External Links
Snippet
Drylands support pastoralist social–ecological systems around the world. Ecological function in these water-limited environments frequently depends on tightly coupled, nonlinear interactions between water, soil, vegetation, and herbivores. Numerous …
- 238000009304 pastoral farming 0 abstract description 168
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
- G06Q10/063—Operations research or analysis
- G06Q10/0639—Performance analysis
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
- G05B13/027—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using neural networks only
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Gomes et al. | Agricultural land fragmentation analysis in a peri-urban context: From the past into the future | |
Gao et al. | Landscape heterogeneity and hydrological processes: a review of landscape-based hydrological models | |
Pretzsch et al. | Forest dynamics, growth, and yield: A review, analysis of the present state, and perspective | |
Gratzer et al. | Spatio‐temporal development of forests–current trends in field methods and models | |
CN116630122B (en) | Lake ecological hydraulic regulation and control method and system based on hydrologic-ecological response relation | |
Franz et al. | An ecohydrological approach to predicting regional woody species distribution patterns in dryland ecosystems | |
Morin et al. | Beyond forest succession: A gap model to study ecosystem functioning and tree community composition under climate change | |
Ortiz et al. | Modelling soil carbon development in Swedish coniferous forest soils—An uncertainty analysis of parameters and model estimates using the GLUE method | |
Santos et al. | Converting conventional ecological datasets in dynamic and dynamic spatially explicit simulations: Current advances and future applications of the Stochastic Dynamic Methodology (StDM) | |
Ross et al. | Comparison of event‐specific rainfall–runoff responses and their controls in contrasting geographic areas | |
Son et al. | Modelling the interaction of climate, forest ecosystem, and hydrology to estimate catchment dissolved organic carbon export | |
Debeljak et al. | Modelling forest growing stock from inventory data: A data mining approach | |
Darby et al. | Modeling apple snail population dynamics on the Everglades landscape | |
Bassiouni et al. | Optimal plant water use strategies explain soil moisture variability | |
Van der Ploeg et al. | Biophysical landscape interactions: Bridging disciplines and scale with connectivity | |
Kabite et al. | Spatiotemporal land cover dynamics and drivers for Dhidhessa River Basin (DRB), Ethiopia | |
Kamali et al. | Improving the simulation of permanent grasslands across Germany by using multi-objective uncertainty-based calibration of plant-water dynamics | |
King et al. | Combining ecohydrologic and transition probability-based modeling to simulate vegetation dynamics in a semi-arid rangeland | |
Eppinga et al. | A new method to infer vegetation boundary movement from ‘snapshot’data | |
Peeters et al. | Conceptual evaluation of continental land-surface model behaviour | |
Crompton et al. | Sensitivity of dryland vegetation patterns to storm characteristics | |
De Michele et al. | A minimal model of soil water–vegetation interactions forced by stochastic rainfall in water-limited ecosystems | |
Carper et al. | Quantifying the transient shock response of dynamic agroecosystem variables for improved socio-environmental resilience. | |
Van der Meersch et al. | Estimating process‐based model parameters from species distribution data using the evolutionary algorithm CMA‐ES | |
White | Predicting Unimpaired Flow in Ungauged Basins:" Random Forests" Applied to California Streams |