Results 121 to 130 of about 4,452 (291)

Estimation under Multicollinearity: Application of Restricted Liu and Maximum Entropy Estimators to the Portland Cement Dataset [PDF]

A high degree of multicollinearity among the explanatory variables severely impairs estimation of regression coefficients by the Ordinary Least Squares. Several methods have been suggested to ameliorate the deleterious effects of multicollinearity.
Mishra, SK
core   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

A Poisson ridge regression estimator [PDF]

The standard statistical method for analyzing count data is the Poisson regression model, which is usually estimated using maximum likelihood (ML) method. The ML method is very sensitive to multicollinearity.
Shukur, Ghazi, Månsson, Kristofer
core  

Ag/Ag2S Nanoparticle‐Based In‐Materio Lightweight Cryptographic System for IoT Edge Security

Advanced Intelligent Systems, EarlyView.
This work presents a nanomaterial‐based in materio encryption method that directly transforms analog signals through nonlinear Ag/Ag2S nanoparticle networks. By exploiting the inherently nonuniform characteristics that arise from random arrangement of nanoparticles as a unique security key, the approach produces highly complex encrypted waveforms ...
Hiroki Tabata, Yuma Yamashita, Yusuke Nakaoka, Oradee Srikimkaew, Muzhen Xu, Yuki Usami, Shunsuke Araki, Hirofumi Tanaka   +7 more
wiley   +1 more source

A New Biased Estimation Class to Combat the Multicollinearity in Regression Models: Modified Two--Parameter Liu Estimator

Computational Journal of Mathematical and Statistical Sciences
The multicollinearity problem occurrence of the explanatory variables affects the least-squares (LS) estimator seriously in the regression models. The multicollinearity adverse effects on the LS estimation are also investigated by many authors.
Mohamed Reda Abonazel
doaj   +1 more source

Time‐Delayed Spiking Reservoir Computing Enables Efficient Time Series Prediction

Advanced Intelligent Systems, EarlyView.
This study proposes time‐delayed spiking reservoir computing (TDSRC) for efficient time series prediction. By concatenating time‐lagged states, TDSRC constructs an expanded readout feature vector without altering internal reservoir dynamics. This approach enables highly accurate forecasting with significantly fewer neurons, providing a resource ...
Pin Jin, Ren Cao, Zhongxue Gan, Siyang Leng   +3 more
wiley   +1 more source

Improved robust ridge regression estimates

Eastern-European Journal of Enterprise Technologies, 2015
У множинній лінійній регресії, коли провісники сильно корельовані, оцінки найменших квадратів (LSE), як правило, дають неточні прогнози. Гребенева регресія, яка грунтується на мінімізації квадратичної функції втрат, чутлива до викидів. Розглянуто дві гладко знижені ψ-функції, засновані на принципі Вінзора, які призводять до асимптотично ефективних ...
openaire   +4 more sources

A note on adaptive generalized ridge regression estimator [PDF]

The problem of estimating parameters in a linear regression model is considered. A class of adaptive generalized ridge estimator is proposed. It is shown that the proposed estimator has smaller mean squared error than the least squares estimator under ...
Wang, Song-Gui, Chow, Shein-Chung
core  

Field‐Programable Dynamics in a Soft Magnetic Actuator Enabling True Random Number Generation and Reservoir Computing

Advanced Intelligent Systems, EarlyView.
Complex dynamics, often avoided in electromechanical design, can enhance soft robotics. We develop durable magnetic soft actuators operating in tunable dynamic regimes, enabling random number generation, stochastic computing, and time‐series prediction.
Eduardo Sergio Oliveros‐Mata, Oleksandr V. Pylypovskyi, Eleonora Raimondo, Rico Illing, Yevhen Zabila, Lin Guo, Guannan Mu, Mónica Navarro López, Xu Wang, Georgios Tzortzinis, Angelos Filippatos, Gilbert Santiago Cañón Bermúdez, Francesca Garescì, Giovanni Finocchio, Denys Makarov   +14 more
wiley   +1 more source