Search Results for "polynomial"

...Solving forward/inverse integro-differential equations (IDEs) [SIAM Rev.] fPINN: solving forward/inverse fractional PDEs (fPDEs) [SIAM J. Sci. Comput.] NN-arbitrary polynomial chaos (NN-aPC): solving forward/inverse stochastic PDEs (sPDEs) [J. Comput. Phys.] PINN with hard constraints (hPINN): solving inverse design/topology optimization [SIAM J. Sci. Comput.] Residual-based adaptive sampling [SIAM Rev., arXiv] Gradient-enhanced PINN (gPINN) [Comput. Methods Appl. Mech. Eng.] PINN with multi-scale Fourier features [Comput. ...

...Created in 2011 and maintained by Renato Alexandre dos Santos Freitas, ATC is designed as a practical Windows desktop application for advanced calculations, automation, and technical problem solving. ATC supports equation solving, polynomial tools, complex numbers, matrix calculations, statistics, physics, geometry, unit conversions, DSP/FFT operations, and scripting. It can also process batch TXT files, making it useful for repeatable calculations and automated workflows. The project also includes ATC Online Alpha, a WebAssembly-based version that brings parts of the ATC engine to the web. ...

NAVAL-SEM is an award-winning, free and open-source offline Structural Equation Modeling (SEM) platform supporting PLS-SEM and CB-SEM workflows. Designed for researchers, PhD scholars, professors, and analysts, it provides visual model building, measurement assessment, structural model analysis, and reproducible research workflows without subscriptions or cloud dependency. Features include: • PLS-SEM & CB-SEM • Bootstrapping, mediation, moderation & conditional process analysis • HTMT,...

python2/3: compute polyfit (1D, 2D, N-D) without any thirdparty library like numpy, scipy etc. also can be used for least squares solution computation and for A=QR matrix decomposition. Tested with python 2.7 and 3.4 Consider donating to this project: https://sourceforge.net/p/purepythonpolyfit/donation For a Sample use, refer to the WIKI

This toolbox contains a set of Python procedures in order to compute examples associated with the computation of Realizable Sign Conditions (RiSC) due to the approach by Basu, Pollack and Roy. The RiSC approach is a way to solve and analyze systems of polynomial equations and inequalities over the real numbers in the field of real-algebraic geometry. The involved computations often consist of highly sophisticated notions, not easy to illustrate by hand. VisualRiSC provides implementations of such notions and functions using the Python package SymPy, on the one hand, and an interface to Gnuplot in order for a visualization of examples using the Python package Gnuplot.py.

Python module for creating functions computing the Cyclic Redundancy Check (CRC). Any generating polynomial producing 8, 16, 24, 32, or 64 bit CRCs is allowed. Generated functions can be used in Python or C/C++ source code can be generated.

This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.