Machine learning
A landmark study published in the Journal of the American College of Cardiology: Heart Failure demonstrates the efficacy of Cardiosense's novel machine learning algorithm in accurately estimating pulmonary capillary wedge pressure (PCWP) in patients with heart failure with reduced ejection fraction (HFrEF) using a noninvasive sensor. The prospective,
Genetic research
Researchers at Guangdong Polytechnic Normal University have developed a new lateral control algorithm that enhances energy-saving performance in intelligent vehicles. The algorithm, dubbed Adaptive Genetic Algorithm LQT Controller, dynamically adjusts parameters to balance global search and local convergence during optimization. According to the study, this approach not only achieves high
Genetic research
Researchers from Tongji University have published a study on safety-prioritized optimization of asteroid sample site selection using a genetic algorithm and variable neighborhood tabu search. According to the study, sample site selection is crucial for asteroid sample return missions, requiring a strategy that considers factors such as terrain and illumination
Genetic research
Researchers from Hubei University of Technology in Wuhan, People's Republic of China, have developed a comprehensive multi-objective optimization framework to address the green vehicle routing problem with time windows (GVRPTWs). This issue remains underexplored in balancing environmental and service quality objectives. The proposed framework aims to minimize total
Genetic research
Researchers at Tokyo University of Science have explored the dynamics of artificial intelligence, revealing a new understanding of biased random walks driven by a dual-choice game. By analyzing the game's outcomes, the team found that a player who employs a genetic algorithm (GA)-based strategy and their opponent
Machine learning
Researchers from Federal University Pernambuco have made significant advancements in predicting dilution in underground mining operations using artificial intelligence. The study highlights the importance of mitigating unplanned dilution caused by blasting inefficiencies or poor rock stability. The research team introduced a statistically rigorous methodology incorporating machine learning algorithms and genetic
Machine learning
Researchers at the Chongqing University of Technology have developed a new machine learning algorithm to estimate the temperature of key components in a vehicle's electric drive system (EDS). The high temperatures of the EDS can affect the performance and reliability of the system, making accurate temperature estimation crucial.
Machine learning
A team of researchers at Hubei University of Technology, led by Jiahui Chen, has made significant strides in machine learning by developing an improved version of the Tyrannosaurus Optimization Algorithm (TROA). The new algorithm, known as ITROA, has been successfully applied to abnormal traffic detection for Software-Defined Networking (SDN), achieving
Machine learning
Researchers from Canakkale Onsekiz Mart University have conducted a study to compare the effectiveness of traditional Multiple Linear Regression (MLR) and deep learning Extreme Gradient Boosting (XGBoost) algorithms in predicting agricultural land prices. The study aimed to examine the relationship between agricultural land prices and economic indicators such as the
Genetic research
Researchers from Guizhou Normal University have developed a novel framework for stroke rehabilitation, utilizing high-density surface electromyography (HD-sEMG) signals and an improved whale optimization algorithm (IWOA)-optimized long short-term memory (LSTM) network. The framework aims to address the limitation of traditional sEMG analysis, which often overlooks the complexity of object-interactive
Machine learning
Researchers at Stanford University are leveraging machine learning to improve the efficacy and safety of targeted cell and gene therapies. By using machine learning algorithms to predict which proteins are more likely to trigger an immune response, the team has made significant progress in designing proteins that avoid such issues
Machine learning
Researchers at the University of Baghdad have developed an effective two-phase phishing detection system, employing unsupervised feature selection and supervised classification. The system utilizes machine learning to precisely identify malicious websites, addressing a critical problem in cybersecurity. The development aims to enhance the accuracy and efficiency of phishing detection, with
