High temporal resolution information on burnt area is needed to improve fire behaviour and emissions models. We used theModerate Resolution Imaging Spectroradiometer (MODIS) thermal anomaly and active fire product (MO(Y)D14) as input to a kriging interpolation to derive continuousmaps of the timing of burnt area for 16 large wildland fires. For each fire, parameters for the kriging model were d...

and Applied Analysis 3 2.2. Universal Kriging for Computing Water Depth in Any Position The basic premise of Kriging interpolation is that every unknown point can be estimated by the weighted sum of the known points: Z∗ 0 n ∑ i 1 λi Zi, 2.1 where Z∗ 0 represents the unknown point, Zi refers to each known point, and λ 0 i is the weight given to it. The Kriging algorithm body is involved in the a...

and Applied Analysis 3

We present a methodology to perform spatial prediction when measured data are curves. In particular, we propose both an estimator of the spatial correlation and a functional kriging predictor. We adapt an optimization criterium used in multivariable spatial prediction in order to estimate the kriging parameters. A real data example on soil penetration resistences illustrates our proposals.

Chaotic particle swarm optimization (CPSO) algorithm is proposed to optimize the Kriging model, which can improve the precision of curve fitting. A typical example is selected to demonstrate the advantage of the optimized Kriging model, compared with other curve fitting tools.

Nonlinear constrained optimization algorithms are widely utilized in artifact design. Certain algorithms also lend themselves well to design of experiments (DOE). Adaptive design refers to experimental design where determining where to sample next is influenced by information from previous experiments. We present a constrained optimization algorithm known as superEGO (a variant of the EGO algor...

The method of stochastic simulation is proposed to model the atmospheric effect on InSAR measurements based on sample data. Test results show that 37.44% reduction in the standard devisation of the atmospheric errors can be achieved with the method of stochastic simulation, compared to 25.69% with the method of Kriging interpolator. The relative improvement of the former over the latter amounts...

In recent decades, the automotive industry has had a constant evolution with consequent enhancement of products quality. industrial applications, quality may be defined as conformance to product specifications and repeatability manufacturing process. Moreover, in modern era Industry 4.0, research on technological innovation made real-time control process possible. Moving from above context, met...

drought monitoring is a fundamental component of drought risk management. it is normally performed usingvarious drought indices that are effectively continuous functions of rainfall and other hydrometeorological variables.in many instances, drought indices are used for monitoring purposes. geostatistical methods allow the interpolationof spatially referenced data and the prediction of values fo...