Based on effectiveness analysis, a novel method is presented for combat aircraft top-hierarchy concept evaluation and decision-making. Applying multi-criterion decision-making (MCDM) and analytic hierarchy process, the new method can help to overcome the limitations of existing evaluation systems and decision-make methods. The proposed method includes the following process~ (1) Establish a multi-criterion and multi-hierarchy evaluation attribute system by introducing combat effectiveness~ (2) Assign weight to the attributes and normalize them; (3) Evaluate and decision-make top-hierarchy aircraft concept based on effectiveness to reach a satisfactory design by comprehensively applying four multi-criterion decision-making methodologies, i.e. grey correlation pro- jection method, weighted summation method, weighted quadrature method and ideal solution decision-making method, while considering the attribute hierarchy system and the logical relations among the attributes. Finally, an example is given to indicate the validity and feasibility of the proposed method. 相似文献
Development of new methods for estimating biophysical parameters can be considered one of the most important targets for the improvement of grassland parameters estimation at full canopy cover. In fact, accurate assessment methods of biophysical characteristics of vegetation are needed in order to avoid the uncertainties of carbon terrestrial sinks.
Remote sensing is a valid tool for scaling up ecosystem measurements towards landscape levels serving a wide range of applications, many of them being related to carbon-cycle models. The aim of this study was to test the suitability of satellite platform sensors in estimating grassland biophysical parameters such as LAI, biomass, phytomass, and Green herbage ratio (GR). Also, we wanted to compare some of the most common NIR and red/green-based vegetation indices with ones that also make use of the MIR band, in relation to their ability to predict grassland biophysical parameters.
Ground-truth measurements were taken on July 2003 and 2004 on the Monte Bondone plateau (Italian Alps, Trento district) in grasslands varying in land use and management intensities. From satellite platforms, an IRS-1C-LISS III image (18/07/2003; 25 m resolution in the visible-NIR and 70 m resolution in the MIR) and a SPOT 5 image (27/07/2004, 10 m resolution in the visible-NIR and MIR) were used.
LAI, biomass, and phytomass measurements showed logarithmic relationships with the investigated NIR and red/green-based indices. GreenNDVI showed the highest R2 values (0.59, IRS 2003; 0.60, SPOT 2004). Index saturation occurred above approximately 100–150 g m−2 of biomass (LAI 1.5–2). On the other hand, GR relationships were shown to be linear. MIR-based indices performed better than NIR and red/green-based ones in estimating biophysical variables, with no saturation effect. Biomass showed a linear regression with Canopy Index (MIR/green ratio) and with the Normalised Canopy Index (NCI) calculated as a normalised difference between MIR and green bands (IRS: R2 = 0.91 and 0.90, respectively. SPOT: R2 = 0.63 and 0.64). Similar correlations could also be found for LAI and phytomass, and GR predictability was shown to be higher than NDVI and GreenNDVI. According to these results obtained in the investigated areas, phytomass, biomass, LAI, and GR are linearly correlated with the investigated MIR band indices and as a result, these parameters could be estimated from the adopted satellite platforms with limited saturation problems. 相似文献
In this paper, we described the Comprehensive AeroSpace Index (CASI), a financial index aimed at representing the economic performance of the aerospace industry. CASI is build upon a data set of approximately 20 years of daily close prices set, from January 1987 to June 2007, from a comprehensive sample of leading aerospace-related companies with stocks negotiated on the New York Exchange (NYSE) and on the over-the-counter (OTC) markets. We also introduced the sub-indices CASI-AERO, for aeronautical segment, and CASI-SAT, for satellite segment, and considered the relation between them. These three indices are compared to others aerospace indices and to more traditional general financial indices like DJIA, S&P500 and Nasdaq. Our results have shown that the CASI is an index that describes very well the aerospace sector behavior, since it is able to reflect the aeronautical segment comportment as well as the satellite one. Therefore, in this sense, it can be considered as a representative index of the aerospace sector. Moreover, the creation of two sub-indices, the CASI-AERO and the CASI-SAT, allows to elucidate capital movements within the aerospace sector, particularly those of speculative nature, like the dot.com bubble and crash of 1998–2001. 相似文献