Results 61 to 70 of about 283,145 (183)

Smart Information Retrieval: Domain Knowledge Centric Optimization Approach

IEEE Access, 2019
In the age of the Internet of Things, online data have witnessed a significant growth in terms of volume and diversity, and research into information retrieval has become one of the important research themes in the Internet-oriented data science research.
Abduladem Aljamel, Taha Osman, Giovanni Acampora, Autilia Vitiello, Ziqi Zhang   +4 more
doaj   +1 more source

Learning curves for Soft Margin Classifiers

, 2002
Typical learning curves for Soft Margin Classifiers (SMCs) learning both realizable and unrealizable tasks are determined using the tools of Statistical Mechanics.
Gordon, Mirta B., Risau-Gusman, Sebastian   +1 more
core   +1 more source

Exploring Kernel Machines and Support Vector Machines: Principles, Techniques, and Future Directions

Mathematics
The kernel method is a tool that converts data to a kernel space where operation can be performed. When converted to a high-dimensional feature space by using kernel functions, the data samples are more likely to be linearly separable.
Ke-Lin Du, Bingchun Jiang, Jiabin Lu, Jingyu Hua, M. N. S. Swamy   +4 more
doaj   +1 more source

Machine Learning Assisted Quality of Transmission Estimation and Planning with Reduced Margins

, 2020
In optical transport networks, the Quality of Transmission (QoT) using a physical layer model (PLM) is estimated before establishing new or reconfiguring established optical connections. Traditionally, high margins are added to account for the model’s inaccuracy and the uncertainty in the current and evolving physical layer conditions, targeting ...
Christodoulopoulos, Konstantinos, Sartzetakis, Ippokratis, Soumplis, Polizois, Varvarigos, Emmanouel   +3 more
openaire   +2 more sources

Comparative Analysis of Machine Learning Models for Predicting Viscosity in Tri-n-Butyl Phosphate Mixtures Using Experimental Data

Computation
Tri-n-butyl phosphate (TBP) is essential in the chemical industry for dissolving and purifying various inorganic acids and metals, especially in hydrometallurgical processes. Recent advancements suggest that machine learning can significantly improve the
Faranak Hatami, Mousa Moradi
doaj   +1 more source

Evaluation of Machine Learning Models in Solar Radiation Prediction for Photovoltaic System Design [PDF]

E3S Web of Conferences
This research evaluates machine learning models in predicting solar radiation, crucial for designing photovoltaic systems. Accuracy in solar forecasting is key to mitigating climate change and meeting energy demand.
Salazar-Achig Roberto, Paguay Alex, Gavilanes Jorge, Salazar-Jácome Elizabeth, Aguirre Yonatan   +4 more
doaj   +1 more source

beta-risk: a New Surrogate Risk for Learning from Weakly Labeled Data

, 2016
International audienceDuring the past few years, the machine learning community has paid attention to developing new methods for learning from weakly labeled data.
Emonet, Rémi, Sebban, Marc, Zantedeschi, Valentina   +2 more
core   +1 more source

The Advanced Actuarial Data Science Based AI-Driven Solutions for Automated Loss Reserving Under IFRS 17 in Non-Life Insurance

Science, Engineering and Technology
This study introduces an AI-driven Automated Actuarial Loss Reserving Model (AALRM) designed to meet IFRS 17 standards for non-life insurance. The model leverages advanced machine learning techniques to improve accuracy, efficiency, and adaptability in ...
Brighton Mahohoho, Charles Chimedza, Florance Matarise, Sheunesu Munyira   +3 more
doaj   +1 more source

Application of various machine learning models for fault detection in the refrigeration system of a brewing company

Engineering and Applied Science Research, 2023
Industrial refrigeration systems typically exhibit a higher energy consumption rate compared to other systems. It is a very important system, and for the brewing industry, it is at the heart of brewing as, in each process, the temperature of the beer ...
Anusak Luekiangkhamla, Natee Panagant, Sujin Bureerat, Nantiwat Pholdee   +3 more
doaj  

Classification with support hyperplanes [PDF]

A new classification method is proposed, called Support Hy-perplanes (SHs). To solve the binary classification task, SHs consider theset of all hyperplanes that do not make classification mistakes, referredto as semi-consistent hyperplanes. A test object
Bioch, J.C., Groenen, P.J.F., Nalbantov, G.I.   +2 more
core   +1 more source