Search Results - (( intelligence based tree algorithm ) OR ( intelligence valid machine algorithm ))

A machine learning approach to predict the activity of smart home inhabitant by Marufuzzaman M., Tumbraegel T., Rahman L.F., Sidek L.M.

Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.] by Mohd, Thuraiya, Jamil, Syafiqah, Masrom, Suraya, Ab Rahim, Norbaya

“…This experiment used five common machine learning algorithms namely 1) Linear Regressor, 2) Decision Tree Regressor, 3) Random Forest Regressor, 4) Ridge Regressor and 5) Lasso Regressor tested on a real estate data-set of covering Kuala Lumpur District, Malaysia. 3 set of experiments was conducted based on the different feature selections and purposes The results show that the implementation of 16 variables based on Experiment 2 has given a promising effect on the model compare the other experiment, and the Random Forest Regressor by using the Split approach for training and validating data-set outperformed other algorithms compared to Cross-Validation approach. …”
Get full text
Get full text

Modeling of static and dynamic components of bio-nanorobotic systems by Gavgani, Hamidreza Khataee

“…In addition, a graph algorithm based on greedy methods is employed to compute a new set of optimal weighted electronic properties of the fullerenes via computing their Minimum Weight Spanning Trees (MWSTs). …”
Get full text
Get full text

Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination by Nallakukkala, Sirisha, Tackie-Otoo, Bennet Nii, Aliyu, Ruwaida, Lal, Bhajan, Nallakukkala, Jagadish Ram Deepak, Devi, Gayathri

“…In this context. ML algorithms provide powerful data driven means to model complex relationship within experimental datasets to improve process optimisation This study systematically evaluated several supervised ML models, including Random Forest (RF) Support Vector Machines (SVM), Ridge Regression, Lasso Regression, Decision Tree, Extra Tree Regression, Gradient Boost, and XGBoost, to predict removal efficiency in GHBD system. …”
Get full text
Get full text

Enhancing fairness and efficiency in teacher placement based on staff placement model: an intelligent teacher placement selection model for Ministry of Education Malaysia by Shamsul Saniron, Zulaiha Ali Othman, Abdul Razak Hamdan

“…The effectiveness of ITPS was evaluated using five machine learning algorithms: J48, Decision Tree, Naïve Bayes, Random Forest, and K-Nearest Neighbors. …”
Get full text
Get full text
Get full text

Ganoderma boninense classification based on near-infrared spectral data using machine learning techniques by Mas Ira Syafila, Mohd Hilmi Tan, Mohd Faizal, Jamlos, Ahmad Fairuz, Omar, Kamarulzaman, Kamarudin, Mohd Aminudin, Jamlos

Get full text
Get full text
Get full text

A comparative study of supervised machine learning approaches for slope failure production by Deris A.M., Solemon B., Omar R.C.

“…The prediction result from testing data was validated based on statistical analysis. The result shows that SVM model has outperformed DT model by giving the prediction accuracy of 97%. ith the advent of technology and the introduction of computational intelligent methods, the prediction of slope failure using the machine learning (ML) approach is rapidly growing for the past few decades. …”

Industrial datasets with ICS testbed and attack detection using machine learning techniques by Mubarak, Sinil, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Balla, Asaad, Tahir, Mohammad, Elsheikh, Elfatih A A, Suliman, F M

Get full text
Get full text
Get full text
Get full text

Improvement on agglomerative hierarchical clustering algorithm based on tree data structure with bidirectional approach by Dalbouh H.A., Md Norwawi N.

Subjects:

Development of a Prediction Algorithm using Boosted Decision Trees for Earlier Diagnoses on Obstructive Sleep Apnea by Sim, Doreen Ying Ying

“…This research develops a knowledge-based system by using computational intelligent approaches based on Boosting algorithms on decision trees augmented by pruning techniques and Association Rule Mining. …”
Get full text
Get full text

E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm by Bouke, Mohamed Aly, Abdullah, Azizol, ALshatebi, Sameer Hamoud, Abdullah, Mohd Taufik

“…The model design is Decision Tree (DT) algorithm-based, with an approach to data balancing since the data set used is highly unbalanced and one more approach for feature selection. …”
Get full text
Get full text

Hybrid Intelligent Warning System for Boiler tube Leak Trips by Singh D., Ismail F.B., Shakir Nasif M.

A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation by Mohd Ali, Nursabillilah, Besar, Rosli, Ab Aziz, Nor Azlina

“…The study involved three machine learning algorithms, random forest (RF), extra tree (ET), and support vector machine (SVM). …”
Get full text
Get full text
Get full text

Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Eight benchmark datasets from UCI were used in the experiments to validate the performance of the proposed algorithms. …”
Get full text
Get full text
Get full text

Intelligent cooperative web caching policies for media objects based on decision tree supervised machine learning algorithm by Ibrahim, Hamidah, Yasin, Waheed, Abdul Hamid, Nor Asilah Wati, Udzir, Nur Izura

“…Moreover, cache pollution is a drawback of traditional web caching policies such as Least Frequently Used (LFU), Least Recently Used (LRU), and Greedy Dual Size (GDS) where web objects that are stored in the cache are not visited frequently. In this work, new intelligent cooperative web caching approaches based on decision tree supervised machine learning algorithm are presented. …”
Get full text
Get full text
Get full text

Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

Subjects:

Solar radiation prediction using boosted decision tree regression model: A case study in Malaysia by Jumin E., Basaruddin F.B., Yusoff Y.B.M., Latif S.D., Ahmed A.N.

Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy by Rahman, Sam Matiur, Ali, Md. Asraf, Altwijri, Omar, Alqahtani, Mahdi, Ahmed, Nasim, Ahamed, Nizam Uddin

“…Therefore, we aimed to classify six classes of freshly excised tissues from a set of electrical impedance measurement variables using five ensemble-based machine learning (ML) algorithms, namely, the random forest (RF), extremely randomized trees (ERT), decision tree (DT), gradient boosting tree (GBT) and AdaBoost (Adaptive Boosting) (ADB) algorithms, which can be subcategorized as bagging and boosting methods. …”
Get full text
Get full text
Get full text

The Implementation of a Machine Learning-based Routing Algorithm in a Lab-Scale Testbed by Ridwan M.A., Radzi N.A.M., Azmi K.H.M., Ahmad A., Abdullah F., Ahmad W.S.H.M.W.

“…Due to network complexity, conventional QoS-improving routing algorithms (RAs) may be impractical. Thus, researchers are developing intelligent RAs, including machine learning (ML)-based algorithms to meet traffic Q oS r equirements. …”

Processing time estimation in precision machining industry using AI / Lim Say Li by Lim, Say Li

“…Keywords: artificial intelligence, artificial neural network, precision machining, time estimation…”
Get full text
Get full text