Results 41 to 50 of about 47,794 (185)

Probabilistic Modeling for Prediction Errors to Enhance Balancing Market Participation of Photovoltaic Systems: Error Threshold Estimation, Multisite Aggregation, and Overloading Effects

Advanced Energy and Sustainability Research, EarlyView.
This study proposes a method to increase the value of solar power in balancing markets by managing prediction errors. The approach models prediction uncertainties and quantifies reserve requirements based on a probabilistic model. This enables the more reliable participation of photovoltaic plants in balancing markets across multiple sites, especially ...
Jindan Cui, Xue Fang, Takashi Oozeki, Yuzuru Ueda   +3 more
wiley   +1 more source

Designing Memristive Materials for Artificial Dynamic Intelligence

Advanced Intelligent Discovery, EarlyView.
Key characteristics required of memristors for realizing next‐generation computing, along with modeling approaches employed to analyze their underlying mechanisms. These modeling techniques span from the atomic scale to the array scale and cover temporal scales ranging from picoseconds to microseconds. Hardware architectures inspired by neural networks
Youngmin Kim, Ho Won Jang
wiley   +1 more source

A Machine Learning Perspective on the Brønsted–Evans–Polanyi Relation in Water‐Gas Shift Catalysis on MXenes

Advanced Intelligent Discovery, EarlyView.
Machine learning predicts activation energies for key steps in the water‐gas shift reaction on 92 MXenes. Random Forest is identified as the most accurate model. Reaction energy and reactant LogP emerge as key descriptors. The approach provides a predictive framework for catalyst design, grounded in density functional theory data and validated through ...
Kais Iben Nassar, Tiago L. P. Galvão, José D. Gouveia, José R. B. Gomes   +3 more
wiley   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source

Thermal Conductance and Mass Transport of Brinkman‐Type Nanofluids Across Porous Plates: A Prabhakar‐Fractional Approach

Asia-Pacific Journal of Chemical Engineering, EarlyView.
ABSTRACT The paper establishes an advanced computing algorithm to investigate the thermosolutal dynamics of an electrically conductive Brinkman‐type nanofluid that moves in a porous channel, and the fluid is acted on by an inclined magnetic field exerted externally.
Urwa Shehbaz, Umair Khan, MD. Shamshuddin, Nermeen Abdullah, Samia Elattar   +4 more
wiley   +1 more source

Self‐Creation of Accelerated Temporal Mirrors

Advanced Physics Research, EarlyView.
The field of temporal analog effects is rapidly emerging and seen as a driver of a paradigm shift in photonics. It promises striking new phenomena but remains experimentally challenging. This work introduces a mechanism that automatically creates a temporal mirror with simple optical means, unlocking practical access to extreme nonlinear dynamics and ...
Oliver Melchert, Surajit Bose, Uwe Morgner, Ihar Babushkin, Ayhan Demircan   +4 more
wiley   +1 more source

Risk‐aware safe reinforcement learning for control of stochastic linear systems

Asian Journal of Control, EarlyView.
Abstract This paper presents a risk‐aware safe reinforcement learning (RL) control design for stochastic discrete‐time linear systems. Rather than using a safety certifier to myopically intervene with the RL controller, a risk‐informed safe controller is also learned besides the RL controller, and the RL and safe controllers are combined together ...
Babak Esmaeili, Nariman Niknejad, Hamidreza Modares   +2 more
wiley   +1 more source

Modeling and parameter estimation for fractional large‐scale interconnected Hammerstein systems

Asian Journal of Control, EarlyView.
Abstract This paper addresses the challenge of modeling and identifying large‐scale interconnected systems exhibiting memory effects, hereditary properties, and non‐local interactions. We propose a fractional‐order extension of the Hammerstein architecture that incorporates Grünwald–Letnikov operators to capture complex dynamics through multiple ...
Mourad Elloumi, Omar Naifar, Imed Bouzida   +2 more
wiley   +1 more source

A Guide to Bayesian Optimization in Bioprocess Engineering

Biotechnology and Bioengineering, EarlyView.
ABSTRACT Bayesian optimization has become widely popular across various experimental sciences due to its favorable attributes: it can handle noisy data, perform well with relatively small data sets, and provide adaptive suggestions for sequential experimentation.
Maximilian Siska, Emma Pajak, Katrin Rosenthal, Antonio del Rio Chanona, Eric von Lieres, Laura M. Helleckes   +5 more
wiley   +1 more source