Search results for " Error."
showing 10 items of 1034 documents
Solution of coupled riccati equations occurring in nash games
2006
To obtain the open-loop Nash strategy for a linear-quadratic differential game, a set of coupled matrix Riccati equations has to be solved. It is shown that by means of algebraic transformations, the original problem can be reduced to another one to which the successive approximation method is applicable. This leads to a simple iterative algorithm with a predetermined approximation error. An example is given to illustrate the proposed method.
Experimental study on triangular central baffle flume
2019
Abstract In this paper the results of the experiments performed to study the flow through a Triangular Central Baffle Flume (TCBF) are reported. The investigated flume consists of a triangular baffle of the apex angle of 75° with a given base width. The theoretical stage-discharge formula was deduced by applying the Buckingham's Theorem and incomplete self-similarity hypothesis and was calibrated using the laboratory measurements carried out in this investigation. The proposed stage-discharge formula is characterized by a mean absolute relative error of 7.4% and 72% of the data points are in an error range of ±5%. The results indicate that TCBF flume is characterized by a flow capacity high…
Predicting sediment deposition rate in check-dams using machine learning techniques and high-resolution DEMs
2021
Sediments accumulated in check dams are a valuable measure to estimate soil erosion rates. Here, geographic information systems (GIS) and three machine learning techniques (MARS-multivariate adaptive regression splines, RF-random forest and SVM-support vector machine) were used, for the first time, to predict sediment deposition rate (SR) in check-dams located in six watersheds in SW Spain. There, 160 dry-stone check dams (~ 77.8 check-dams km−2), accumulated sediments during a period that varied from 11 to 23 years. The SR was estimated in former research using a topographical method and a high-resolution Digital Elevation Model (DEM) (average of 0.14 m3 ha−1 year−1). Nine environmental-to…
Use of Guided Regularized Random Forest for Biophysical Parameter Retrieval
2018
This paper introduces a feature selection method based on random forest -the Guided Regularized Random Forest (GRRF)- which can be used in classification and regression tasks. The method is based on the regularization of the information gain in the random forest nodes to obtain a subset of relevant and non-redundant features. The proposed method is used as a preliminary step In the process of retrieving biophysical parameters from a hyperspectral image. Preliminary experiments show that we can reduce the RMSE of the retrievals by around 7% for the Leaf Area Index and around 8% for the fraction of vegetation cover when compared to the results using random forest features.
Some Examples for Solving Clinical Problems Using Neural Networks
2001
In this paper neural networks are presented for solving some pharmaceutical problems. We have predicted and prevented patients with potential risk of post-Chemotherapy Emesis and potentially intoxicated patients treated with Digoxin. Neural networks have been also used for predicting Cyclosporine A concentration and Erythropoietin concentrations. Several neural networks (multilayer perceptron for classification tasks and Elman and FIR networks for prediction) and classical methods have been used. Results show how neural networks are very suitable tools for classification and prediction tasks, outperforming the classical methods. In a neural approach it is not strictly necessary to assume a …
Parameter optimization for amplify-and-forward relaying with imperfect channel estimation
2009
Cooperative diversity is a promising technology for future wireless networks. In this paper, we consider a cooperative communication system operating in an amplify-and-forward (AF) mode with an imperfectly-known relay fading channel. It is assumed that a pilot symbol assisted modulation (PSAM) scheme with linear minimum mean square estimator (LMMSE) is used for the channel estimation. A simple and easy-to-evaluate asymptotical upper bound (AUB) of the symbol-error-rate (SER) is derived for uncoded AF cooperative systems with quadrature amplitude modulation (QAM) constellations. Based on the AUB, we propose a criterion for the choice of parameters in the PSAM scheme, i.e., the pilot spacing …
A three-factor optimisation strategy for micellar liquid chromatography
2000
An interpretive optimisation methodology for micellar liquid chromatography (MLC) is shown, taking into account pH, surfactant (sodium dodecyl sulphate) and organic modifier (propanol) concentration. Two objectives are considered: to develop a highly practical straightforward three-factor optimisation for practical MLC, and, in order to avoid unecessary experiments, to link two and three-factor optimisations through a step-wise construction of the experimental design at different pH levels. The whole pH range for an ODS column (from 3 to 7) is covered. The proposed strategy was thoroughly evaluated using the chromatographic data from 81 experimental mobile phases, applied to the separation …
Advantages of fitting contrast curves using logistic function: a technical note.
2013
Objective The aim of this article is to demonstrate how the contrast properties of an imaging system can be ideally fitted with the use of stripe patterns and the logistic function. Study Design Stripe patterns with defined amounts of line pairs (lp/mm) per mm (10-20 lp/mm) were recorded with the use of digital photostimulable storage phosphor. Scan data and normalized image data were analyzed with the use of ImageJ and MatLab to calculate different contrast curves. Results For original scan data, the goodness of fit was 0.0000019 (sum of squared error [SSE]). The R-square was 0.9998. For normalized data the goodness of fit was 0.0007 (SSE) and the R-square 0.998. An amount of 50% contrast …
Demultiplexing Visible and Near-Infrared Information in Single-Sensor Multispectral Imaging
2016
In this paper, we study a single-sensor imaging system that uses a multispectral filter array to spectrally sample the scene. Our system captures information in both visible and near-infrared bands of the electromagnetic spectrum. Due to manufacturing limitations, the visible filters in this system also transmit the NIR radiation. Similarly, visible light is transmitted by the NIR filter, leading to inaccurate mixed spectral measurements. We present an algorithm that resolves this issue by separating NIR and visible information. Our method achieves this goal by exploiting the correlation of multispectral images in both spatial and spectral domains. Simulation results show that the mean squa…
Therapeutic Drug Monitoring of Kidney Transplant Recipients Using Profiled Support Vector Machines
2007
This paper proposes a twofold approach for therapeutic drug monitoring (TDM) of kidney recipients using support vector machines (SVMs), for both predicting and detecting Cyclosporine A (CyA) blood concentrations. The final goal is to build useful, robust, and ultimately understandable models for individualizing the dosage of CyA. We compare SVMs with several neural network models, such as the multilayer perceptron (MLP), the Elman recurrent network, finite/infinite impulse response networks, and neural network ARMAX approaches. In addition, we present a profile-dependent SVM (PD-SVM), which incorporates a priori knowledge in both tasks. Models are compared numerically, statistically, and in…