Software Listing of Author : "Xlpert Analytics"

User-friendly (see screenshot) Minimum knowledge of neural net technology Number of inputs and outputs are limited only by MS Excel limitation Can accommodate more than 2 outputs nodes. Most commercial available software is limited to one output node MS Excel graphing and data manipulation capabilities Pre-processing and data scaling option Detail network model reports for creating error distribution graph, actual vs forecasted graph, correlation graph etc.. Sypnapses screen where user can watch network model activities on the fly 3 or 4 layer network architecture option 3 types of training option i.e. backpropagation with momemtum, conjugate gradient and genetic optimization Single point and bulk prediction capabilities

  • Platform: Win2000, Win7 x32, Win7 x64, WinOther, WinVista, WinVista x64

OptimuStock is the new generation of intelligent forecasting software based on neural network technology. Don’t be intimidated by these terms. You don’t need to be an expert in artificial intelligence to use our software. In just 3 clicks, you can start to predict the stock prices. Generally, OptimuStock use the ability of nonlinear machine learning models to forecast market direction/prices using technical indicators and fundamental data as features. OptimuStock is the only forecasting Excel add in with an automatic neural network architecture and parameters selection. It gives you access to breakthrough algorithms for automatic data preprocessing and neural network preparation inside MS Excel. With these algorithms, you do not need to have any prior experience in statistics or artificial intelligence to exploit the power of...

  • Platform: Win7 x32, WinOther, WinVista
  • xl bit
  • License: Demo
  • Price: 35

User-friendly and no programming needed. (see screenshot) Very similar to Excel Solver set up. Maximum 500 population allowed. 3 choices of crossover methods. (see screenshot) Adjustable crossover and mutation rates. Unlimited variables in one optimization problem. (Depend on user computer speed and memory) Two types of fitness scaling. (see screenshot) Multiple fitness functions. 4 type of variables i.e. binary, integer, non-integer and permutation. Adjustable random number seed so that user can use same set of initial population with different GA parameters. Example files provided. Full report and fitness graph. (see screenshot) see variables changes on the fly. (see screenshot) adjust crossover and mutation rate on the fly. Top six solutions are shown in report.

  • Platform: Win7 x32, Win7 x64, WinOther, WinVista, WinVista x64
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