Results 51 to 60 of about 173,823 (173)

Alpha MAML: Adaptive Model-Agnostic Meta-Learning

, 2019
Model-agnostic meta-learning (MAML) is a meta-learning technique to train a model on a multitude of learning tasks in a way that primes the model for few-shot learning of new tasks.
Baydin, Atılım Güneş, Behl, Harkirat Singh, Torr, Philip H. S.   +2 more
core  

Perbandingan Algoritma Machine Learning Menggunakan Pemilihan Fitur Chi-square dalam Pengklasifikasian Penyakit Jantung

Jurnal Saintekom
Heart disease is one of the deadliest diseases worldwide. This condition often presents symptoms that do not immediately cause severe effects on the sufferer, making early anticipation crucial.
Hirmayanti Hirmayanti, Ema Utami
doaj   +1 more source

AI-Driven Methane Emission Prediction in Rice Paddies: A Machine Learning and Explainability Framework

Methane
Rice cultivation accounts for roughly 10% of worldwide anthropogenic greenhouse gas emissions, making it a significant source of methane (CH4) Despite modest observational constraints, estimates of worldwide CH4 emissions from rice agriculture range from
Abira Sengupta, Fathima Nuzla Ismail, Shanika Amarasoma   +2 more
doaj   +1 more source

Enhancing Photovoltaic Energy Output Predictions Using ANN and DNN: A Hyperparameter Optimization Approach

Energies
This study investigates the use of artificial neural networks (ANNs) and deep neural networks (DNNs) for estimating photovoltaic (PV) energy output, with a particular focus on hyperparameter tuning.
Atıl Emre Cosgun
doaj   +1 more source

Enhanced Heart Disease Diagnosis Using Machine Learning Algorithms: A Comparison of Feature Selection

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Heart disease or cardiovascular disease is one of the leading causes of death in the world. Based on WHO data, in 2019, as many as 17.9 million people died from cardiovascular disease.
Hirmayanti, Ema Utami
doaj   +1 more source

Improved Pacific Decadal Oscillation Prediction by an Optimizing Model Combined Bidirectional Long Short-Term Memory and Multiple Modal Decomposition

Remote Sensing
The Pacific Decadal Oscillation (PDO), as the dominant mode of decadal sea surface temperature variability in the North Pacific, exhibits both interannual and decadal fluctuations that significantly influence global climate.
Hang Yu, Junbo Lei, Pengfei Lin, Tao Zhang, Hailong Liu, Huilin Lai, Lindong Lai, Bowen Zhao, Bo Wu   +8 more
doaj   +1 more source

Hyperparameter Learning via Distributional Transfer

, 2018
Bayesian optimisation is a popular technique for hyperparameter learning but typically requires initial exploration even in cases where similar prior tasks have been solved. We propose to transfer information across tasks using learnt representations of training datasets used in those tasks.
Law, HCL, Zhao, P, Chan, L, Huang, J, Sejdinovic, D   +4 more
openaire   +3 more sources

Predicting Liquid Natural Gas Consumption via the Multilayer Perceptron Algorithm Using Bayesian Hyperparameter Autotuning

Energies
Reductions in energy consumption and greenhouse gas emissions are required globally. Under this background, the Multilayer Perceptron machine-learning algorithm was used to predict liquid natural gas consumption to improve energy consumption efficiency ...
Hyungah Lee, Woojin Cho, Jong-hyeok Park, Jae-hoi Gu   +3 more
doaj   +1 more source

Strongly Versus Weakly Coupled Data Assimilation in Coupled Systems With Various Inter‐Compartment Interactions

Journal of Advances in Modeling Earth Systems
Coupled data assimilation (CDA) has been attracting researchers' interests to improve Earth system modeling. The CDA methods are classified into two: weakly coupled data assimilation (wCDA), which considers cross‐compartment interaction only in a ...
Norihiro Miwa, Yohei Sawada
doaj   +1 more source

Object Detection with Hyperparameter and Image Enhancement Optimisation for a Smart and Lean Pick-and-Place Solution

Signals
Pick-and-place operations are an integral part of robotic automation and smart manufacturing. By utilizing deep learning techniques on resource-constraint embedded devices, the pick-and-place operations can be made more accurate, efficient, and ...
Elven Kee, Jun Jie Chong, Zi Jie Choong, Michael Lau   +3 more
doaj   +1 more source