Results 71 to 80 of about 1,047,164 (269)
Performance evaluation of photovoltaic scenario generation
Frontiers in PhysicsPhotovoltaic scenario generation plays a critical role in power systems characterized by high diversity and fluctuation. Despite recent theoretical advancements, effectively evaluating the performance of photovoltaic scenario generation remains a ...
Siyu Ren +6 more
doaj +1 more source
Autoregressive Text Generation Beyond Feedback Loops [PDF]
arXiv, 2019 Autoregressive state transitions, where predictions are conditioned on past predictions, are the predominant choice for both deterministic and stochastic sequential models. However, autoregressive feedback exposes the evolution of the hidden state trajectory to potential biases from well-known train-test discrepancies.
arxiv
Advanced Intelligent Systems, EarlyView.Recent advancements in wearable healthcare have brought accessible continuous glucose monitoring systems (CGMs) for diabetes management. To address the limitations of CGMs, closed‐loop systems utilizing monitored glucose levels for insulin dosing are being developed.
Wei Huang +5 more
wiley +1 more source
Exploring the Frontier: Generative AI Applications in Online Consumer Behavior Analytics
Management Letters/Cuadernos de GestiónThis paper presents a systematic review of the application of generative artificial intelligence (AI) in online consumer behavior analytics (OCBA). With the advent of e-commerce and social media, consumer behavior increasingly occurs online, generating ...
Takuma Kimura
doaj +1 more source
Prediction of Arctic Sea Ice Concentration Using a Fully Data Driven Deep Neural Network
Remote Sensing, 2017 The Arctic sea ice is an important indicator of the progress of global warming and climate change. Prediction of Arctic sea ice concentration has been investigated by many disciplines and predictions have been made using a variety of methods.
Junhwa Chi, Hyun-choel Kim
doaj +1 more source
Fast Structured Decoding for Sequence Models [PDF]
arXiv, 2019 Autoregressive sequence models achieve state-of-the-art performance in domains like machine translation. However, due to the autoregressive factorization nature, these models suffer from heavy latency during inference. Recently, non-autoregressive sequence models were proposed to reduce the inference time. However, these models assume that the decoding
arxiv
Applied Artificial Intelligence in Materials Science and Material Design
Advanced Intelligent Systems, EarlyView.AI‐driven methods are transforming materials science by accelerating material discovery, design, and analysis, leveraging large datasets to enhance predictive modeling and streamline experimental techniques. This review highlights advancements in AI applications across spectroscopy, microscopy, and molecular design, enabling efficient material ...
Emigdio Chávez‐Angel +7 more
wiley +1 more source
EnergiesPower system stability (PSS) refers to the capacity of an electrical system to maintain a consistent equilibrium between the generation and consumption of electric power. In this paper, the PSS is evaluated for a “hybrid power plant” (HPP) which combines
Théodore Desiré Tchokomani Moukam +3 more
doaj +1 more source
Series Arc Fault Detection Algorithm Based on Autoregressive Bispectrum Analysis
Algorithms, 2015 Arc fault is one of the most critical reasons for electrical fires. Due to the diversity, randomness and concealment of arc faults in low-voltage circuits, it is difficult for general methods to protect all loads from series arc faults. From the analysis
Kai Yang +5 more
doaj +1 more source
Advanced Intelligent Systems, EarlyView.This article develops a novel feedback structure for machine learning‐based anomaly forecasting, by which both forecasting the future states and detecting the anomalies in these states can be achieved at the same time. The algorithm is shown to be applicable to power systems, verifying its effectiveness in detecting potential faults before they occur ...
Hyung Tae Choi +3 more
wiley +1 more source