Search Results - (( using formulation based algorithm ) OR ( using vectorization learning algorithm ))

Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. …”
Get full text
Get full text
Get full text

A hybrid residue based sequential encoding mechanism with XGBoost improved ensemble model for identifying 5-hydroxymethylcytosine modifications by Uddin I., Awan H.H., Khalid M., Khan S., Akbar S., Sarker M.R., Abdolrasol M.G.M., Alghamdi T.A.H.

“…To address this challenge, the paper proposed XGB5hmC, a machine learning algorithm based on a robust gradient boosting algorithm (XGBoost), with different residue based formulation methods to identify 5hmC samples. …”

Quantum-Behaved Lightning Search Algorithm to Improve Indirect Field-Oriented Fuzzy-PI Control for im Drive by Hannan M.A., Ali J.A., Mohamed A., Amirulddin U.A.U., Tan N.M.L., Uddin M.N.

Combining cluster quality index and supervised learning to predict students’ academic performance by Suhaila Zainudin, Rapi’ah Ibrahim, Hafiz Mohd Sarim

“…The best cluster is further analysed using classification to predict students’ academic performance. …”
Get full text
Get full text
Get full text

Super resolution imaging using modified lanr based on separable filtering by Somadina, Ike Chidiebere

“…Super resolution is then achieved using the regularized patch representation (projection matrix) learned to predict the high resolution image features. …”
Get full text
Get full text

Restoration of blurred images using geometric and chebichef moments / Ahlad Kumar by Ahlad, Kumar

“…In the first method, the framework of variational method is formulated in moment domain to implement deblurring of the Gaussian and motion blurred images using Euler-Lagrange identity and alternate minimization (AM) algorithm. …”
Get full text
Get full text

Hybrid Soft Computing Approach for Determining Water Quality Indicator: Euphrates River by Jing, Li, Husam Ali , Abdulmohsin, Samer Sami , Hasan, Li , Kaiming, Belal , Al-Khateeb, Mazen Ismaeel, Ghareb, Mohammed, Muamer N.

“…In this research, the implementation of hybrid evolutionary model based on integrated support vector regression (SVR) with firefly algorithm (FFA) was investigated for water quality indicator prediction. …”
Get full text
Get full text
Get full text
Get full text

Ensemble learning using multi-objective optimisation for arabic handwritten words by Ghadhban, Haitham Qutaiba

“…Multi-Objective Ensemble Oriented (MOEO) formulated to control the classifier topology and provide feedback support for changing the classifiers' topology and weights based on the extension of Non-dominated Sorting Genetic Algorithm (NSGA-II). …”
Get full text
Get full text
Get full text
Get full text

Bayesian network of influence of sociodemographic variables on dengue related knowledge, attitude, and practices in selected areas in Selangor, Malaysia by Ajibola, Lamidi-Sarumoh Alaba

“…The data collected was used to learn the structure of BN via some known algorithms using R programming language. …”
Get full text
Get full text

Neuro – Genetic model for the projection of crude oil price capable of handling of uncertainty / Haruna Chiroma by Haruna , Chiroma

“…This study presents an alternative model based on Neural Network and Genetic Algorithm (Neuro-Genetic) for the projection of crude oil price while considering the impact of uncertainties. …”
Get full text
Get full text
Get full text

Specific heat capacity extraction of soybean oil/mxene nanofluids using optimized long short-term memory by Qazani, Mohammad Reza Chalak, Aslfattahi, Navid, Kulish, Vladimir Vladimirovich, Asadi, Houshyar, Schmirler, Michal, Zakarya, Muhammad, Alizadehsani, Roohallah, Haleem, Muhammad, Kadirgama, Kumaran

“…Notably, 95% of the recorded data via differential scanning calorimetry (DSC) is used for training machine learning techniques. In comparison, 5% is used for testing and validation purposes of the developed algorithm. …”
Get full text
Get full text
Get full text

Investigation of machine learning models in predicting compressive strength for ultra-high-performance geopolymer concrete: A comparative study by Abdellatief M., Hassan Y.M., Elnabwy M.T., Wong L.S., Chin R.J., Mo K.H.

“…Overall, the dataset of 128 CS results was used to develop the machine learning (ML) models. …”

Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

“…For water level prediction, lagged rainfall and water level are used. In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”

Support directional shifting vector: A direction based machine learning classifier by Kowsher, Md., Hossen, Imran, Tahabilder, Anik, Prottasha, Nusrat Jahan, Habib, Kaiser, Zafril Rizal, M Azmi

“…In this article, we have focused on developing a model of angular nature that performs supervised classification. Here, we have used two shifting vectors named Support Direction Vector (SDV) and Support Origin Vector (SOV) to form a linear function. …”
Get full text
Get full text
Get full text

Global spatial suitability mapping of wind and solar systems using an explainable aI-based approach by Sachit, Mourtadha Sarhan, Mohd Shafri, Helmi Zulhaidi, Abdullah, Ahmad Fikri, Mohd Rafie, Azmin Shakrine, Gibril, Mohamed Barakat A.

“…Real-world renewable energy experiences (more than 55,000 on-site wind and solar plants worldwide) are exploited to train three machine learning (ML) algorithms, namely Random Forest (RF), Support Vector Machine (SVM), and Multi-layer Perceptron (MLP). …”
Get full text
Get full text

Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China by Sattar Hanoon M., Najah Ahmed A., Razzaq A., Oudah A.Y., Alkhayyat A., Feng Huang Y., kumar P., El-Shafie A.

“…Therefore, this study investigates the capability of various machine learning algorithms in predicting the power production of a reservoir located in China using data from 1979 to 2016. …”

Geospatial AI-based approach to assess the spatiotemporal suitability of onshore wind-solar farms in Iraq by Sachit, Mourtadha Sarhan Almushattat

“…In this context, global geospatial data for 13 conditioning factors were collected, and 55,619 inventory samples of wind and solar stations worldwide were prepared to train three machine learning (ML) algorithms, namely Random Forest (RF), Support Vector Machine (SVM), and Multi-Layer Perceptron (MLP). …”
Get full text
Get full text
Get full text

Machine Learning Algorithms for Diabetes Prediction: A Review Paper by Al-Sideiri A., Cob Z.B.C., Drus S.B.M.

Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

“…Most of the currently existing intrusion detection systems (IDS) use machine learning algorithms to detect network intrusion. …”
Get full text
Get full text

Multivariate Based Analysis of Methane Adsorption Correlated to Toc and Mineralogy Impact from Different Shale Fabrics by Irfan, S.A., Azli, N.M., Abdulkareem, F.A., Padmanabhan, E.

“…The variation of adsorption on shale fabric has been conducted using different machine learning approaches. The multivariate analysis is carried out using the partial least square (PLS) method and support vector regression (SVR), along with random forest regression method. …”
Get full text
Get full text