An Improved and Explainable Electricity Price Forecasting Model via SHAP-Based Error Compensation Approach

Engineering, Energy Engineering, Information Science, Electronic Information, Artificial Intelligence,
electricity price forecasting   explainable artificial intelligence   SHAP method   error compensation   neural networks   electricity markets   price volatility  

Improved Electricity Price Forecasting Model Based on SHAP and Its Explainability Analysis Background and Research Motivation Electricity price forecasting (EPF) models have become a hot research topic in recent years, particularly due to the financial impact of market volatility on stakeholders. Especially in European energy markets, recent years ...

Multiobjective Dynamic Flexible Job Shop Scheduling with Biased Objectives via Multitask Genetic Programming

Engineering, Mechanical Engineering, Information Science, Computer Science, Automation, Artificial Intelligence,
dynamic scheduling   flexible job shop   genetic programming   multitask learning   multiobjective optimization   scheduling heuristics   algorithm efficiency  

Breakthrough Research in Multiobjective Dynamic Flexible Job Shop Scheduling: An Innovative Approach to Optimize Biased Objectives via Multitask Learning in Genetic Programming Background Introduction Dynamic Flexible Job Shop Scheduling (DFJSS) is an essential combinatorial optimization problem with extensive real-world applications in areas such ...

NPE-DRL: Enhancing Perception-Constrained Obstacle Avoidance with Nonexpert Policy-Guided Reinforcement Learning

Engineering, Aerospace Engineering, Information Science, Computer Science, Artificial Intelligence,
UAVs   Obstacle avoidance   Deep reinforcement learning   Nonexpert policy   Perception-constrained   Sample efficiency   Monocular vision  

Research on Improving UAV Obstacle Avoidance in Vision-Constrained Environments Based on Nonexpert Policy Reinforcement Learning In recent years, unmanned aerial vehicles (UAVs) have gained widespread application in civilian fields such as package delivery, risk assessment, and emergency rescue, owing to their superior maneuverability and versatili...

Learning Neural Network Classifiers by Distributing Nearest Neighbors on Adaptive Hypersphere

Learning Neural Network Classifiers by Distributing Nearest Neighbors on Adaptive Hypersphere

Information Science, Computer Science, Artificial Intelligence,
neural network classifiers   adaptive hypersphere   nearest neighbors   contrastive loss   local optima   embedding space scalability  

Adaptive Hypersphere Neural Network Classifier: Overview of ASNN Research Introduction and Research Background In recent years, with the development of artificial intelligence and deep learning, neural networks (NNs) have been widely applied to classification tasks. The essence of these tasks lies in establishing decision boundaries through neural ...

Knowledge Probabilization in Ensemble Distillation: Improving Accuracy and Uncertainty Quantification for Object Detectors

Information Science, Computer Science, Artificial Intelligence,
knowledge probabilization   ensemble distillation   object detection   uncertainty quantification   deep neural networks   accuracy improvement   feature knowledge  

Research on the Application of Knowledge Probabilization in Ensemble Distillation Academic Background: Significance of the Research and Problem Statement In recent years, deep neural networks (DNNs) have found broad applications in safety-critical fields such as autonomous driving, medical diagnosis, and climate prediction due to their outstanding ...

Efficient CORDIC-based Activation Function Implementations for RNN Acceleration on FPGAs

Engineering, Electrical Engineering, Information Science, Electronic Information, Computer Science, Artificial Intelligence,
CORDIC   RNN   activation function   FPGA   hardware acceleration   natural language processing   edge devices  

Efficient Implementation of RNN Activation Functions: Breakthroughs in CORDIC Algorithms and FPGA Hardware Acceleration Background and Research Significance In recent years, with the rapid advancement of deep learning technologies, Recurrent Neural Networks (RNNs), particularly Long Short-Term Memory (LSTM) networks, have demonstrated powerful capa...

Boosting Few-Shot Semantic Segmentation with Prior-Driven Edge Feature Enhancement Network

Boosting Few-Shot Semantic Segmentation with Prior-Driven Edge Feature Enhancement Network

Information Science, Computer Science, Artificial Intelligence,
few-shot learning   semantic segmentation   edge features   prior information   deep learning   object boundaries   edge enhancement  

A New Approach to Enhance Few-Shot Semantic Segmentation: Prior-Driven Edge Feature Enhancement Network In the field of artificial intelligence, semantic segmentation is a core technology in computer vision that aims to assign semantic category labels to every pixel in an image. However, traditional semantic segmentation methods rely on large amoun...

Phase 1/2 Trial of Brogidirsen: Dual-Targeting Antisense Oligonucleotides for Exon 44 Skipping in Duchenne Muscular Dystrophy

Medicine, Medical Laboratory Science, Neurology, Life Sciences, Biochemistry, Bioengineering, Immunology, Genetics,
Duchenne muscular dystrophy   exon skipping   antisense oligonucleotide   dual-targeting   Brogidirsen   biomarkers   muscle function stabilization  

New Advances in Dual-Targeting Antisense Oligonucleotide Therapy for Duchenne Muscular Dystrophy: Phase 1⁄2 Clinical Trial of Brogidirsen Background Duchenne Muscular Dystrophy (DMD) is a fatal genetic disorder primarily affecting skeletal and cardiac muscles, leading to early loss of mobility and, eventually, organ failure. Currently, there is no ...

Hormone Therapy Enhances Anti-PD1 Efficacy in Premenopausal Estrogen Receptor-Positive and HER2-Negative Advanced Breast Cancer

Medicine, Rheumatology and Immunology, Endocrinology, Oncology, Life Sciences, Cell Biology, Biochemistry, Immunology,
hormone therapy   anti-PD1 antibody   estrogen receptor-positive breast cancer   HER2-negative   immune microenvironment   tumor immunotherapy  

Hormone Therapy Enhances Anti-PD-1 Efficacy: A Breakthrough Study Targeting Estrogen Receptor-Positive/HER2-Negative Metastatic Breast Cancer Background: Why Conduct This Study? In recent years, cancer immunotherapies have achieved transformative success, with notable efficacy in “hot tumors,” such as triple-negative breast cancer (TNBC), which hav...

High Cellular Plasticity State of Medulloblastoma: Local Recurrence and Distant Dissemination

Medicine, Neurology, Oncology, Life Sciences, Cell Biology, Biochemistry, Immunology,
medulloblastoma   cellular plasticity   recurrence   dissemination   PTPRZ1   tumor subpopulations   therapeutic target  

High Cellular Plasticity State of Pediatric Medulloblastoma: A Comprehensive Analysis of Local Recurrence and Distant Dissemination Research Background Medulloblastoma (MB) is a highly heterogeneous pediatric intracranial malignancy. While current treatments (surgery, radiotherapy, and chemotherapy) improve survival rates after initial treatment, r...