The Print

Leveraging AI and Machine Learning for Intelligent Portfolio Management

Artificial intelligence and machine learning are reshaping how investors build and maintain portfolios. These tools bring ...
Hosted on MSN

RMSProp Optimization from Scratch in Python

Understand and implement the RMSProp optimization algorithm in Python. Essential for training deep neural networks efficiently. #RMSProp #Optimization #DeepLearning Trump Cuts Millions After ...
Frontiers

Identifying the optimal ratio from protein foods for protein and nutrient quality in plant-based meals using a non-linear optimization approach

Background: Plant-based diets with reduced animal protein intake are increasingly recommended for health and sustainability reasons that have potential implications for nutrient intake, including ...
SciELO

A Heuristic Algorithm Based on Line-up Competition and Generalized Pattern Search for Solving Integer and Mixed Integer Non-linear Optimization Problems

The global optimization of integer and mixed integer non-linear problems has a lot of applications in engineering. In this paper a heuristic algorithm is developed using line-up competition and ...
Scientific Research Publishing

Huan, T.T. and Anh, H.P.H. (2019) Optimal Stable Gait for Nonlinear Uncertain Humanoid Robot Using Central Force Optimization Algorithm. Engineering Computations, 36, 599-621.

ABSTRACT: This note describes optimally matching the seminal Fano Load using Central Force Optimization with Negative Gravity. This approach improves the best fitness by more than eighteen percent and ...
GitHub

andreas-apostolatos/Engineering-Design-Optimization-using-MATLAB-and-Python

This workshop on Engineering Design Optimization using MATLAB® and Python™ addresses the shape optimization of mechanical components for strength. Python ...
C&EN

Mixed-Integer Linear Programming Formulation with Embedded Machine Learning Surrogates for the Design of Chemical Process Families

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. There is a need for design strategies that can support rapid and widespread deployment ...
IEEE

Accelerated Successive Convex Approximation for Nonlinear Optimization-Based Control

Abstract: The successive convex approximation (SCA) methods stand out as the viable option for nonlinear optimization-based control, as it effectively addresses the challenges posed by nonlinear ...