The sea-level disturbances caused by meteorological event of June and July 2002 at Algiers Harbour is examined by spectral analysis applied to the original signal measured tide gauge with a frequency sampling of 0.003 Hz. Finally, the configured methodology is deployed in a user-friendly web application. The comparative study results in the most efficient damage index, as well as the most promising machine learning algorithm in predicting the structural response of a reinforced concrete building under single or multiple seismic events. The structural analyses are performed considering both real and artificial ground motion sequences, while the structural damage is expressed in terms of two overall damage indices. From this point of view, the initial damage state of the structural system, as well as 16 well-known ground motion intensity measures, are adopted as the features of the machine-learning algorithms that aim to predict the structural damage after each seismic event. In the present study, the capability of ten machine learning algorithms to predict the structural damage of an 8-storey reinforced concrete frame building subjected to single and successive ground motions is examined. We quantify the information gain associated with using 3B42RT in the probabilistic model instead of relying only on Climate 2015, 3 330 climatology and show that the quantitative precipitation estimates produced by this model are well calibrated compared to APHRODITE.Īdvanced machine learning algorithms have the potential to be successfully applied to many areas of system modelling.
![gnu octave gnu octave](https://www.saashub.com/images/app/context_images/6/507620898293/gnu-octave-alternatives-medium.png)
We find that 3B42RT, which is freely available in near real time, has reasonable correspondence with ground-based precipitation products on a daily timescale rank correlation coefficients approach 0.6, almost as high as the retrospectively calibrated TMPA 3B42 product. We compared the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42RT product with individual stations and with the gridded APHRODITE product to evaluate its ability to retrieve different precipitation intensities. Here, we extend our analysis to the daily and subdaily timescales, which are relevant for mapping the hazards caused by storms as well as drought. Satellite-based precipitation products have been shown to represent precipitation well over Nepal at monthly resolution, compared to ground-based stations.
![gnu octave gnu octave](https://img-16.ccm2.net/yOsiKM0l1c7_wU3dHP-_Yef1hFs=/4a80680e49ed48238d96b4ab747670bf/ccm-download/RWUe7tVap2Gsr7gW.png)
The graphical representation of the concentration of chemical species is also possible as a function of selected variables, such as the initial concentration or the volume of a given reagent.
![gnu octave gnu octave](https://ewh.ieee.org/sb/el_salvador/uca/images/gnu-octave.png)
The approach also allows multiple calculations by automatic changing of the initial conditions.
#Gnu octave software
The exact solution of the system of non-linear equations describing the multiple equilibria is obtained by means of the fsolve tool of the open source software OCTAVE. The method consists in writing down a system of non-linear equations formed by equilibrium constant expressions and the needed number of conservation balances so to match the number of chemical species involved. Two practical examples of different complexity are proposed in this work to show the application of a general systematic approach for the numerical calculation of multi-equilibria problems, regardless of the number or types of equilibria involved. It allows the treatment of complex problems without the need of simplifications, and the outcome of a very large number of calculations in a short time. The use of computational software can greatly facilitate the teaching of chemical equilibria.