Results 291 to 300 of about 1,466,211 (327)

Mathematics of multi-agent learning systems at the interface of game theory and artificial intelligence

Science China Information Sciences
Evolutionary Game Theory (EGT) and Artificial Intelligence (AI) are two fields that, at first glance, might seem distinct, but they have notable connections and intersections.
Long Wang, Feng Fu, Xingru Chen
semanticscholar   +1 more source

Improvement of Power Systems Stability Using a New Learning Algorithm Based on Lyapunov Theory for Neural Network

Iranian Journal of Science and Technology, Transactions of Electrical Engineering, 2017
In this paper, a new learning algorithm based on Lyapunov stability theory for neural networks is used to improve the power system stability. During the online control process, the identification of system is not necessary, because of learning ability of the proposed controller.
Mehdi Arab Sadegh, Mohsen Farahani
openalex   +3 more sources

Stability and NMR Chemical Shift of Amorphous Precursors of Methane Hydrate: Insights from Dispersion-Corrected Density Functional Theory Calculations Combined with Machine Learning

The Journal of Physical Chemistry B, 2020
Clathrate hydrates of natural gases are important backup energy sources. It is thus of great significance to explore the nucleation process of hydrates. Hydrate clusters are building blocks of crystalline hydrates and represent the initial stage of hydrate nucleation.
Keyao Li, Pengju Wang, Lingli Tang, Ruili Shi, Yan Su, Jijun Zhao   +5 more
openalex   +5 more sources

An Interval Type-3 Fuzzy System and a New Online Fractional-Order Learning Algorithm: Theory and Practice

IEEE transactions on fuzzy systems, 2020
The main reason of the extensive usage of the fuzzy systems in many branches of science is their approximation ability. In this paper, an interval type-3 fuzzy system (IT3FS) is proposed.
A. Mohammadzadeh, Mohammad Hosein Sabzalian, Weidong Zhang   +2 more
semanticscholar   +1 more source

Thermodynamic Stability Landscape of Halide Double Perovskites via High‐Throughput Computing and Machine Learning

Advanced Functional Materials, 2019
Formability and stability issues are of core importance and difficulty in current research and applications of perovskites. Nevertheless, over the past century, determination of the formability and stability of perovskites has relied on semiempirical ...
Zhenzhu Li, Qichen Xu, Qingde Sun, Z. Hou, W. Yin   +4 more
semanticscholar   +1 more source

The DFT and Machine Learning Method Accelerated the Discovery of DMSCs with High ORR and OER Catalytic Activities.

Journal of Physical Chemistry Letters
The oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER) are crucial for the conversion of clean energy. Recently, dual-metal-site catalysts (DMSCs) have gained much attention due to their high atom utilization, stronger stability, and
Zhaolin Fang, Shuyuan Li, Yunjiang Zhang, Yaxin Wang, Kong Meng, Chenyu Huang, Shaorui Sun   +6 more
semanticscholar   +1 more source

Inherent Trade-Offs between Diversity and Stability in Multi-Task Benchmarks

International Conference on Machine Learning
We examine multi-task benchmarks in machine learning through the lens of social choice theory. We draw an analogy between benchmarks and electoral systems, where models are candidates and tasks are voters. This suggests a distinction between cardinal and
Guanhua Zhang, Moritz Hardt
semanticscholar   +1 more source

Stability of spectral learning algorithms: theory, methodologies and applications

In Data Mining an important research problem is the identification and analysis of theoretical properties that characterize and explain the behavior of learning algorithms. Based on such theoretical tools the comparison and analysis of algorithms can be based on rigorous and sound criteria other than simply their empirical behavior. In this context, an
openaire   +1 more source

Transient-Stability-Aware Frequency Provision in IBR-Rich Grids via Information Gap Decision Theory and Deep Learning

This paper introduces a framework to address the critical loss of transient stability caused by reduced inertia in grids with high inverter-based resource (IBR) penetration. The proposed method integrates a predictive deep learning (DL) model with information gap decision theory (IGDT) to create a risk-averse dispatch strategy.
Masoumi, Amin, Korkali, Mert
openaire   +1 more source

Extendable Machine Learning Model for the Stability of Single Atom Alloys

Topics in catalysis, 2020
Karun K. Rao, Q. Do, Khoa Pham, D. Maiti, L. Grabow   +4 more
semanticscholar   +1 more source