PROBLEM TO BE SOLVED: To provide a fitness group training method in which a user avoids injuring a leg due to overtraining and achieves effective results. A fitness group training method accelerates the speed of each running machine until the pulse value falls within a predetermined first pulse ...
Protein-ligand binding affinity prediction is a key element of computer-aided drug discovery. Most of the existing deep learning methods for protein-ligand binding affinity prediction utilize single models and suffer from low accuracy and generalization
The increasing level of physical fitness among soccer players necessitates the exploration of alternative training methods to enhance overall performance. Perceptual–cognitive skills are crucial for sport-specific capabilities such as decision making and reactive agility, enabling athletes to extract visual ...
"speed play" in Swedish; training involves varying the intensity of exercise (often running) cross training involves using a variety of activities to develop a general fitness circuit training involves doing a number of different exercises one after another for short, set periods of time weight tra...
VO2max has long been used as a primary measure of an individual’s cardiorespiratory fitness, and as a marker of training effect [5]. The interplay betweenVO2max and running economy determines vVO2max [2,6], whereas the MMSS (e.g., second lactate threshold) establishes the limit of ...
(LDA) as a main feature extraction technique. The prediction of fitness assessment of students' attributes on agility and speed was based on a cost-effective neural network approach with precision, recall, f1-score, and area under the curve was predicted as 63.6%, 87%, 79.8%, and 85.95. ...
“all-day pace” that is a speed you could do all day. In running its “easy” running. I like to call it “pissing around'”intensity. It barely feels like you’re doing anything at all but the stimulus in this case comes from the sheer volume (and frequency) of training being ...
Genetic algorithms and genetic programming calculate a fitness value for each individual in a population, and select individuals with high fitness values for the mating pool with high probability to produce the next generation through the exchange of genetic material and mutations between individuals. ...
The present study examines the role of feature selection methods in optimizing machine learning algorithms for predicting heart disease. The Cleveland Heart disease dataset with sixteen feature selection techniques in three categories of filter, wrapper,
Secondly, the proposed and finalized technique incorporates use of customized Regressors in NARX technique for precise speed prediction. The customized Regressors improve predictive accuracy by achieving 99.1% training, 98.01% validation and above 90% accuracy in real-world signal testing even under noisy...