Search alternatives:
models optimization » level optimization (Expand Search), motor optimization (Expand Search), mongoose optimization (Expand Search)
binary data » binary rat (Expand Search)
binary ai » binary rat (Expand Search)
models optimization » level optimization (Expand Search), motor optimization (Expand Search), mongoose optimization (Expand Search)
binary data » binary rat (Expand Search)
binary ai » binary rat (Expand Search)
-
1
-
2
-
3
A Hybrid Approach for Predicting Critical Machining Conditions in Titanium Alloy Slot Milling Using Feature Selection and Binary Whale Optimization Algorithm
Published 2023“…In this study, features were extracted from signals in time, frequency, and time–frequency domains. The t-test and the binary whale optimization algorithm (BWOA) were applied to choose the best features and train the support vector machine (SVM) model with validation and training data. …”
-
4
Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine
Published 2024“…In this MOD-POA+ELM algorithm, the modified pelican optimization algorithm (MOD-POA) has been utilized to optimize the parameters of ELM’s hidden neurons. …”
-
5
A method for data path synthesis using neural networks
Published 2017“…Presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …”
Get full text
Get full text
Get full text
Get full text
conferenceObject -
6
A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata
Published 2025Get full text
doctoralThesis -
7
A hybrid model to predict the pressure gradient for the liquid-liquid flow in both horizontal and inclined pipes for unknown flow patterns
Published 2023“…The important feature subset is identified using the modified Binary Grey Wolf Optimization Particle Swarm Optimization (BGWOPSO) algorithm. …”
-
8
Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes
Published 2025“…We evaluated thirteen machine learning models at each stage, selecting the top-performing classifiers to optimize results. …”