作者: 辯論的終結(jié) 時(shí)間: 2025-3-21 21:58
Soft Mapping of Coastal Vegetation from Remotely Sensed Imagery with a Feed-Forward Neuronal Networkng and monitoring vegetation has, however, frequently not been fully realized. Of the many reasons for this, one major limitation has been the reliance on conventional supervised image classification approaches as the tool for mapping.作者: nurture 時(shí)間: 2025-3-22 02:17
Ultrafast Estimation of Neotropical Forest , Distributions from Ground Based Photographs Using a Neuand vegetal species, with relevant and long-ranged interactions (Charles-Dominique 1995a). A drastic simplification is thus necessary if one wants to develop a manageable model, and for this it is essential to find sets of easily measured synthetic macroscopic variables.作者: Consensus 時(shí)間: 2025-3-22 05:46 作者: DUST 時(shí)間: 2025-3-22 09:24 作者: 總 時(shí)間: 2025-3-22 14:40
Patterning of Community Changes in Benthic Macroinvertebrates Collected from Urbanized Streams for tladecek 1979; Hellawell 1986). Methods for characterizing ’changes’ in communities are needed in terms of predicting the future development of the community, detecting mechanism of community differentiation, and assessing ecological status of the target ecosystem.作者: 熱情的我 時(shí)間: 2025-3-22 18:46 作者: 組成 時(shí)間: 2025-3-22 21:48 作者: Tortuous 時(shí)間: 2025-3-23 04:00 作者: monogamy 時(shí)間: 2025-3-23 05:33 作者: 浪費(fèi)物質(zhì) 時(shí)間: 2025-3-23 12:21 作者: 污點(diǎn) 時(shí)間: 2025-3-23 16:07 作者: 專橫 時(shí)間: 2025-3-23 18:56 作者: angiography 時(shí)間: 2025-3-24 01:45 作者: AGGER 時(shí)間: 2025-3-24 05:09
The Use of Fibrin Glue in Tympanoplastyen made to increase the richness of such pixel based classifications by, for example, relating the probability of class membership of pixels in particular classes to the sub-pixel area occupied by those classes (Foody 1996a).作者: 小步走路 時(shí)間: 2025-3-24 06:59 作者: Excise 時(shí)間: 2025-3-24 14:09
Fibrin Sealant in Tracheobronchial Surgeryductive modelling are regression analysis and neuronal network training. Deductive modelling goes much further towards integration of structured and aggregated ecological data into relevant ecological theory (see Fig. 10.1). Deductive modelling is normally based on physical mass balances for food webs and nutrient cycles, or heuristic rule sets.作者: AORTA 時(shí)間: 2025-3-24 16:36
H. A. Henrich,B. Stitz,F. Conrading environmental systems. They have been used in studies in this and related papers, to model environmental influences on the impact of tropospheric ozone pollution on plants (Balls et al. 1995; Balls et al. 1996; Roadknight et al. 1997; Ball et al. 1998).作者: A保存的 時(shí)間: 2025-3-24 21:18
Hemangioma Treatment with Fibrin Sealantng. Supervised learning can be applied to the classification of individuals of unknown origin among already well-defined groups: This has been successfully applied to genetic data on bees (Conuet et al. 1996, with some phylogenetically well separated lineages), and on trout(Aurelle et al. 1998, but with some less clearly differentiated groups).作者: 辯論 時(shí)間: 2025-3-25 02:51 作者: 斜 時(shí)間: 2025-3-25 05:17 作者: Resection 時(shí)間: 2025-3-25 08:41 作者: 獸群 時(shí)間: 2025-3-25 12:56
Predicting Ecologically Important Vegetation Variables from Remotely Sensed Optical/Radar Data Usingbiosphere/atmosphere interactions, and carbon dynamics (Asrar and Dozier 1994; Hall et al. 1995). The success of efforts to extract vegetation variables such as these from remotely sensed data and available ancillary data will determine the degree and scope of vegetation-related science performed using EOS data.作者: avenge 時(shí)間: 2025-3-25 17:50 作者: 夜晚 時(shí)間: 2025-3-25 22:27 作者: floaters 時(shí)間: 2025-3-26 02:20 作者: 權(quán)宜之計(jì) 時(shí)間: 2025-3-26 04:26 作者: Orgasm 時(shí)間: 2025-3-26 12:07
Predicting Ecologically Important Vegetation Variables from Remotely Sensed Optical/Radar Data Usingharton and Myers 1997). The satellite digital data sets and ancillary data products will require the development of efficient algorithms that can incorporate and functionally utilize disparate data types. Numerous vegetation variables, e.g. leaf area, height, canopy roughness, land cover, stomatal r作者: CREEK 時(shí)間: 2025-3-26 12:51
Soft Mapping of Coastal Vegetation from Remotely Sensed Imagery with a Feed-Forward Neuronal Networkoor quality (Williams 1994; DeFries and Townshend 1994). Often the only practicable means of acquiring data on vegetation distribution at appropriate spatial and temporal resolutions is through remote sensing (Townshend et al. 1991; Skole 1994). The considerable potential of remote sensing for mappi作者: 處理 時(shí)間: 2025-3-26 20:17 作者: 群島 時(shí)間: 2025-3-26 23:18
Normalized Difference Vegetation Index Estimation in Grasslands of Patagonia by ANN Analysis of Satecorrelation with biophysical rates of the target area, such as transpiration or primary productivity (Sellers et al. 1992). . has been shown to be a linear estimator of the fraction of the photosynthetic active radiation (PAR) absorbed by the canopy (Potter et al. 1993; Ruimy et al. 1994). Monteith 作者: Anecdote 時(shí)間: 2025-3-27 04:41 作者: 保存 時(shí)間: 2025-3-27 06:18 作者: 兇兆 時(shí)間: 2025-3-27 11:06 作者: Omniscient 時(shí)間: 2025-3-27 15:08
Predicting Presence of Fish Species in the Seine River Basin Using Artificial Neuronal Networksey can be considered to be good indicators of the health of aquatic ecosystems (Fausch et al. 1990). This paradigm is the basis for using biological monitoring of fish to assess environmental degradation (Karr 1987).作者: 松馳 時(shí)間: 2025-3-27 17:53
Elucidation and Prediction of Aquatic Ecosystems by Artificial Neuronal Networkslands, and rivers. Two modelling approaches are distinguished to achieve these aims: inductive and deductive modelling. Inductive modelling is considered to be the result of structuring, aggregation, or pattern extraction of ecological data (see Fig. 10.1). The most comon techniques available for in作者: 催眠 時(shí)間: 2025-3-28 01:52 作者: jealousy 時(shí)間: 2025-3-28 04:55
A Comparison of Artificial Neuronal Network and Conventional Statistical Techniques for Analysing En distributions in oceans (Simpson et al. 1992), grassland community changes (Tan and Smeins 1996), and in the recognition of birdsong (McIlraith and Card 1997). They are well suited to modelling complex nonlinear systems which are inherently ‘noisy,’ a characteristic that makes them suited to modell作者: 泄露 時(shí)間: 2025-3-28 10:20
Application of the Self-Organizing Mapping and Fuzzy Clustering to Microsatellite Data: How to Detecre less used in ecology and populations genetics, recent studies have shown that they can be very efficient for such problems (Cornuet et al. 1996; Foody 1997; Mastrorillo et al. 1997; Guégan et al. 1998). ANNs have several advantages: they can be applied to various data, from environmental variable作者: 休息 時(shí)間: 2025-3-28 13:44
The Macroepidemiology of Parasitic and Infectious Diseases: A Comparative Study Using Artificial Neur about 16 percent, are strictly dependent on humans for their survival (Ashford 1991; Petney and Andrews 1998).For the few West European countries providing reasonably reliable demographic data before the nineteenth century, epidemics, famines and wars are favoured as the three critical controlling作者: 組成 時(shí)間: 2025-3-28 18:30
Evolutionarily Optimal Networks for Controlling Energy Allocation to Growth, Reproduction and Repairquantitatively, using an evolutionary optimization approach, the so-called disposable soma theory of ageing (Kirkwood 1981). This theory affirms that the senescence of an organism with age is due to insufficient repair caused by evolutionarily profitable diversion of energy to the organism’s other n作者: 模范 時(shí)間: 2025-3-28 22:45
https://doi.org/10.1007/978-3-642-57030-8Tempo; algorithms; artificial neural network; ecology; ecosystem; ecosystem ecology; evolution; fuzzy; genet作者: BOOM 時(shí)間: 2025-3-28 23:30
978-3-642-63116-0Springer-Verlag Berlin Heidelberg 2000作者: 業(yè)余愛好者 時(shí)間: 2025-3-29 05:38 作者: MULTI 時(shí)間: 2025-3-29 09:59
Predicting Presence of Fish Species in the Seine River Basin Using Artificial Neuronal Networksey can be considered to be good indicators of the health of aquatic ecosystems (Fausch et al. 1990). This paradigm is the basis for using biological monitoring of fish to assess environmental degradation (Karr 1987).作者: Connotation 時(shí)間: 2025-3-29 15:06
Performance Comparison between Regression and Neuronal Network Models for Forecasting Pacific Sardinvasive characteristics which can undermine one’s ability to conduct accurate forecasts. In some cases the span or resolution of available data can limit development or use of a particular kind of model.作者: 有害 時(shí)間: 2025-3-29 17:09 作者: 兒童 時(shí)間: 2025-3-29 22:51 作者: 美麗的寫 時(shí)間: 2025-3-30 01:48 作者: HARD 時(shí)間: 2025-3-30 06:10
https://doi.org/10.1007/978-3-642-82880-5al, mathematical, and statistical methods to techniques originating from artificial intelligence (Ackley et al. 1985) like expert systems (Bradshaw et al. 1991; Recknagel et al. 1994), genetic algorithms (d’Angelo et al. 1995; Golikov et al. 1995) and artificial neuronal networks, i.e. ANN (Colasant作者: cloture 時(shí)間: 2025-3-30 12:05
