AIMC Topic: Algorithms

Clear Filters Showing 13201 to 13210 of 28713 articles

Packaging Big Data Visualization Based on Computational Intelligence Information Design.

Computational intelligence and neuroscience
A method based on a computational intelligence information model is proposed to study the visualization of large data packages. Since the CAIM algorithm only considers the distribution of the largest number of classes in an interval, it offers an opt...

Research on Impulse Power Load Forecasting Based on Improved Recurrent Neural Networks.

Computational intelligence and neuroscience
Deep learning is good at extracting the required feature quantity from the massive input information through multiple hidden layers and completing the learning through training to achieve the task of load forecasting. The impulse power load data cont...

Clustering high-dimensional data via feature selection.

Biometrics
High-dimensional clustering analysis is a challenging problem in statistics and machine learning, with broad applications such as the analysis of microarray data and RNA-seq data. In this paper, we propose a new clustering procedure called spectral c...

Basic principles of AI simplified for a Medical Practitioner: Pearls and Pitfalls in Evaluating AI algorithms.

Current problems in diagnostic radiology
With the rapid integration of artificial intelligence into medical practice, there has been an exponential increase in the number of scientific papers and industry players offering models designed for various tasks. Understanding these, however, is d...

A new deep learning framework based on blood pressure range constraint for continuous cuffless BP estimation.

Neural networks : the official journal of the International Neural Network Society
Blood pressure (BP) is known as an indicator of human health status, and regular measurement is helpful for early detection of cardiovascular diseases. Traditional techniques for measuring BP are either invasive or cuff-based and thus are not suitabl...

Sparse factorization of square matrices with application to neural attention modeling.

Neural networks : the official journal of the International Neural Network Society
Square matrices appear in many machine learning problems and models. Optimization over a large square matrix is expensive in memory and in time. Therefore an economic approximation is needed. Conventional approximation approaches factorize the square...

Artificial neural networks for the prediction of biochar yield: A comparative study of metaheuristic algorithms.

Bioresource technology
In this study, an integrated framework of artificial neural networks (ANNs) and metaheuristic algorithms have been developed for the prediction of biochar yield using biomass characteristics and pyrolysis process conditions. Comparative analysis of s...

Automatic Implementation Algorithm of Pressure Relief Drilling Depth Based on an Innovative Monitoring-While-Drilling Method.

Sensors (Basel, Switzerland)
An innovative monitoring-while-drilling method of pressure relief drilling was proposed in a previous study, and the periodic appearance of amplitude concentrated enlargement zone in vibration signals can represent the drilling depth. However, there ...

Real-Time Fault Detection and Condition Monitoring for Industrial Autonomous Transfer Vehicles Utilizing Edge Artificial Intelligence.

Sensors (Basel, Switzerland)
Early fault detection and real-time condition monitoring systems have become quite significant for today's modern industrial systems. In a high volume of manufacturing facilities, fleets of equipment are expected to operate uninterrupted for days or ...

Machine learning to predict pregnancy outcomes: a systematic review, synthesizing framework and future research agenda.

BMC pregnancy and childbirth
Machine Learning (ML) has been widely used in predicting the mode of childbirth and assessing the potential maternal risks during pregnancy. The primary aim of this review study is to explore current research and development perspectives that utilize...