Results 121 to 130 of about 23,749 (256)

An Entropic Approach to Constrained Linear Regression

Mathematics
We introduce a novel entropy minimization approach for the solution of constrained linear regression problems. Rather than minimizing the quadratic error, our method minimizes the Fermi–Dirac entropy, with the problem data incorporated as constraints. In
Argimiro Arratia, Henryk Gzyl
doaj   +1 more source

ParamNet: A Physics‐Guided Deep Learning Framework for Intelligent Self‐Inversion of Vacuum Optical Levitation Systems

Advanced Intelligent Systems, EarlyView.
A physics‐guided deep learning framework, ParamNet, is introduced for the intelligent self‐inversion of vacuum optical tweezers. By fuzing dual‐branch time–frequency features with physical dynamical constraints, it achieves high‐accuracy calibration of trap parameters from short‐window, low‐frequency trajectories, outperforming traditional methods ...
Qi Zheng, Wenfeng Fan, Feng Li, Jian Wu, Wei Quan   +4 more
wiley   +1 more source

Review on Isotonic and Convex Regression

Shape-restricted regression provides a framework for estimating an unknown regression function $f_0: \Omega \subset \mathbb{R}^d \rightarrow \mathbb{R}$ from noisy observations \((\boldsymbol{X}_1, Y_1), \ldots, (\boldsymbol{X}_n, Y_n)\) when no explicit functional relationship between $\boldsymbol{X}$ and $Y$ is known, but $f_0$ is assumed to satisfy ...
openaire   +1 more source

Talk to Your Data: An Agentic Artificial Intelligence‐Driven Decision‐Support Framework for Prosumer Energy Optimization and Recommendations

Advanced Intelligent Systems, EarlyView.
An agentic AI‐driven decision‐support framework for prosumers is proposed, integrating PV generation, load profiling, and multihorizon optimization within a four‐agent architecture. The approach significantly reduces grid dependence, enhances self‐sufficiency and prevents system oversizing.
Adela BÂRA, Simona‐Vasilica OPREA
wiley   +1 more source

An Elegant Multi-Agent Gradient Descent for Effective Optimization in Neural Network Training and Beyond

Applied Sciences
Non-convex optimization problems often challenge gradient-based algorithms, such as Gradient Descent. Neural network training, a prominent application of gradient-based methods, heavily relies on their computational efficiency. However, the cost function
Mohammad Sakka, Mohammad Reza Bahrami
doaj   +1 more source

Overcoming the Phase Discontinuity Problem in RIS Optimization: A Robust and Scalable Phase‐Aware Deep Regression Framework via Hybrid CNN–LSTM Architecture

Advanced Intelligent Systems, EarlyView.
The phase discontinuity problem—where the cyclic nature of phase angles causes catastrophic errors near the ±π boundary—is a fundamental obstacle in learning‐based reconfigurable intelligent surface (RIS) optimization. A phase‐aware hybrid CNN–LSTM framework resolves this by decomposing phase predictions into sine–cosine components, mapping circular ...
Seda Savaşçı Şen, Ali Çalhan, Murtaza Cicioğlu, Oğuzhan Demiryürek   +3 more
wiley   +1 more source

Studying the Thermodynamic Phase Stability of Organic–Inorganic Hybrid Perovskites Using Machine Learning

Molecules
As an important photovoltaic material, organic–inorganic hybrid perovskites have attracted much attention in the field of solar cells, but their instability is one of the main challenges limiting their commercial application.
Juan Wang, Xinzhong Wang, Shun Feng, Zongcheng Miao   +3 more
doaj   +1 more source

Assessment of In Vitro Nano‐Cytotoxicity Through Fluorescence Microscopy via Neural Network‐Based Live/Dead Cell Classification

Advanced Intelligent Systems, EarlyView.
FluoAI is a two‐stage, label‐free method for quantifying nanomaterial‐induced cytotoxicity from conventional fluorescence microscopy images. Mask R‐CNN segmentation and DenseNet‐121 classification provide rapid live/dead classification matching human accuracy.
Ugur C. Topkiran, Ali Gasimli, Lal Durmaz, Diya Vashani, Himish Paul, Giridhar R. Akkaraju, Anton V. Naumov   +6 more
wiley   +1 more source

Food inflation pass‐through from agricultural imports in a small open economy

American Journal of Agricultural Economics, EarlyView.
Abstract This paper develops a new framework for quantifying cost pass‐through in a small open economy by estimating firm‐level markup responses to agricultural import price shocks. We show theoretically that markup adjustments depend on firms' reliance on imported inputs and demand curvature, generating heterogeneous inflationary effects across firm ...
Minseong Kang, Seungki Lee
wiley   +1 more source

Crop insurance and irrigation behavior: The conditional role of pumping costs

American Journal of Agricultural Economics, EarlyView.
Abstract Excessive water use for irrigation can accelerate the depletion of water resources, undermining agriculture's resilience to weather‐related shocks. Understanding how farmers make water use decisions is essential for developing effective water management policies.
Sungmin Cheu, Molly Sears
wiley   +1 more source