Solving MIN UR problem by triangle evolution algorithm with archiving and niche techniques

In this paper, as an extension of minimum unsatisfied linear relations problem (MIN ULR), the minimum unsatisfied relations (MIN UR) problem is investigated. A triangle evolution algorithm with archiving and niche techniques is proposed for MIN UR problem. Different with algorithms in literature, it solves MIN problem directly, rather than transforming it into many sub-problems. The proposed algorithm is also applicable for the special case of MIN UR, in which it involves some mandatory relations. Numerical results show that the algorithm is effective for MIN UR problem and it outperforms Sadegh's algorithm in sense of the resulted minimum inconsistency number, even though the test problems are linear.

A finite-element algorithm for modeling variably saturated flows

A general numerical algorithm in the context of finite element scheme is developed to solve Richards’ equation, in which a mass-conservative, modified head based scheme (MHB) is proposed to approximate the governing equation, and mass-lumping techniques are used to keep the numerical simulation stable. The MHB scheme is compared with the modified Picard iteration scheme (MPI) in a ponding infiltration example. Although the MHB scheme is a little inferior to the MPI scheme in respect of mass balance, it is superior in convergence character and simplicity. Fully implicit, explicit and geometric average conductivity methods are performed and compared, the first one is superior in simulation accuracy and can use large time-step size, but the others are superior in iteration efficiency. The algorithm works well over a wide variety of problems, such as infiltration fronts, steady-state and transient water tables, and transient seepage faces, as demonstrated by its performance against published experimental data. The algorithm is presented in sufficient detail to facilitate its implementation.

New uniform algorithm to predict reversed phase retention values under different gradient conditions

A new numerical emulation algorithm was established to calculate retention parameters in RP-HPLC with several retention times under different linear or nonlinear binary gradient elution conditions and further predict the retention time under any other binary gradient conditions. A program was written according to this algorithm and nine solutes were used to test the program. The prediction results were excellent. The maximum relative error of predicted retention time was less than 0.45%. (C) 2002 Elsevier Science B.V. All rights reserved.

accurate and self-consistent ocean color algorithm:simultaneous retrieval of aerosol optical properties and chlorphyll concentrations

A new algorithm has been developed for simultaneous retrieval of aerosol optical properties and chlorophyll concentrations in case I waters. This algorithm is based on an improved complete model for the inherent optical properties and accurate simulations of the radiative transfer process in the coupled atmosphere-ocean system. It has been tested against synthetic radiances generated for the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) channels and has been shown to be robust and accurate. A unique feature of this algorithm is that it uses the measured radiances in both near-IR and visible channels to find that combination of chlorophyll concentration and aerosol optical properties that minimizes the error across the spectrum. Thus the error in the retrieved quantities can be quantified.

Application of Dempster-Shafer evidence theory to unsupervised classification in multisource remote sensing

The aim of this paper is to show that Dempster-Shafer evidence theory may be successfully applied to unsupervised classification in multisource remote sensing. Dempster-Shafer formulation allows for consideration of unions of classes, and to represent both imprecision and uncertainty, through the definition of belief and plausibility functions. These two functions, derived from mass function, are generally chosen in a supervised way. In this paper, the authors describe an unsupervised method, based on the comparison of monosource classification results, to select the classes necessary for Dempster-Shafer evidence combination and to define their mass functions. Data fusion is then performed, discarding invalid clusters (e.g. corresponding to conflicting information) thank to an iterative process. Unsupervised multisource classification algorithm is applied to MAC-Europe'91 multisensor airborne campaign data collected over the Orgeval French site. Classification results using different combinations of sensors (TMS and AirSAR) or wavelengths (L- and C-bands) are compared. Performance of data fusion is evaluated in terms of identification of land cover types. The best results are obtained when all three data sets are used. Furthermore, some other combinations of data are tried, and their ability to discriminate between the different land cover types is quantified