In this tutorial, we will see how to build a neural network with backpropagation in Excel. We’ll use simple formulas and functions to create our neural network and will provide clear and easily ...

Conclusion: Algorithm is modified to minimize the costs of the errors made. Experiment shows that including misclassification cost in the form of learning rate while training backpropagation algorithm ...

Slower convergence and longer training times are the disadvantages often mentioned when the conventional backpropagation (BP) algorithm are compared with other competing techniques. In addition, in ...

Backpropagation learning algorithm for multilayer perceptrons (MLPs) has disadvantages of slow convergence and easily being trapped into local optimum. Inspired by efficient global searching ability ...

Build your own backpropagation algorithm from scratch using Python — perfect for hands-on learners! An Air India Boeing 787 flying to London with over 240 people on board crashed shortly after ...

Citation: Li C, Liang G, Zhao H and Chen G (2021) A Demand-Side Load Event Detection Algorithm Based on Wide-Deep Neural Networks and Randomized Sparse Backpropagation. Front. Energy Res. 9:720831.

Neural networks using the backpropagation algorithm were biologically “unrealistic in almost every respect” he said. For one thing, neurons mostly send information in one direction.