Search Results - (( variable reducing learning algorithm ) OR ( java application reoptimize algorithm ))

Optimizing dam and reservoir operations using machine learning by Mohammad Abdullah Adib Almubaidin

Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms by Ziyad Sami B.H., Ziyad Sami B.F., Kumar P., Ahmed A.N., Amieghemen G.E., Sherif M.M., El-Shafie A.

“…In this research, machine learning algorithms including regression models, tree regression models, support vector regression (SVR), ensemble regression (ER), and gaussian process regression (GPR) were utilized to predict the compressive and tensile concrete strength. …”

Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining by Sivarao, Subramonian

“…One such method is machine learning, which involves using a computer algorithm to capture hidden knowledge from data. …”
Get full text
Get full text

Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
Get full text
Get full text

SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

“…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
Get full text
Get full text

Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

“…This thesis expects an enhancement algorithm to be able to reduce a false positive alarm and misclassification rate. …”
Get full text
Get full text

Gas Identi cation by Using a Cluster-k-Nearest-Neighbor by Brahim Belhaouari, samir

Get full text
Get full text

A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

“…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
Get full text

Performance analysis of machine learning algorithms for missing value imputation by Zainal Abidin, Nadzurah, Ismail, Amelia Ritahani, Emran, Nurul Akmar

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

Biodiesel synthesis from Ceiba pentandra oil by microwave irradiation-assisted transesterification: ELM modeling and optimization by Silitonga A.S., Shamsuddin A.H., Mahlia T.M.I., Milano J., Kusumo F., Siswantoro J., Dharma S., Sebayang A.H., Masjuki H.H., Ong H.C.

Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications by Shanmugam Y., Narayanamoorthi R., Ramachandaramurthy V.K., Bernat P., Shrestha N., Son J., Williamson S.S.

“…The learning algorithms consider variables such as core structure, cross-coupling effect, and coil flux pipe length. …”

The impact of the combat method on radiomics feature compensation and analysis of scanners from different manufacturers by Zhang, Xiaolei, Iqbal bin Saripan, M., Wu, Yanjun, Wang, Zhongxiao, Wen, Dong, Cao, Zhendong, Wang, Bingzhen, Xu, Shiqi, Liu, Yanli, Marhaban, Mohammad Hamiruce, Dong, Xianling

“…Conclusions: The Combat algorithm has reduced variability in radiomic features from different scanners. …”
Get full text
Get full text
Get full text

Predictive Modelling of Stroke Occurrence among Patients using Machine Learning by Sures, Narayasamy, Thilagamalar, Maniam

“…Advanced machine learning algorithms, including logistic regression, decision trees, random forests, and support vector machines, were utilized to analyses the dataset and develop a predictive model. …”
Get full text
Get full text
Get full text
Get full text

Automated model selection for corporation credit risk assessment using machine learning / Zulkifli Halim by Halim, Zulkifli

“…The models are based on the four machine learning algorithms: logistic regression, support vector machine, decision tree, and neural network; two ensemble techniques: adaptive boost and bootstrap aggregation; three deep learning algorithms: recurrent neural network, long short-term memory(LSTM), and gated recurrent unit (GRU). …”
Get full text
Get full text

Performance analysis of machine learning algorithms for missing value imputation by Ismail, Amelia Ritahani, Zainal Abidin, Nadzurah, Emran, Nurul Akmar

Get full text
Get full text
Get full text

Random forest algorithm for co2 water alternating gas incremental recovery factor prediction by Belazreg, L., Mahmood, S.M., Aulia, A.

“…Predictive tools based on machine learning are gaining in popularity in the E&P industry by enhancing conventional procedures and reducing operational cost under current unstable oil market. …”
Get full text
Get full text

Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management by almahameed, Bader aldeen, Bisharah, Majdi

“…The Voting regression, which leverages the collective predictive power of multiple models, exhibits superior performance in comparison to individual algorithms. Feature selection methods play a crucial role in identifying the variables that have a significant impact on project costs. …”
Get full text
Get full text

Modelling and investigating the impacts of climatic variables on ozone concentration in Malaysia using correlation analysis with random forest, decision tree regression, linear reg... by Balogun, A.-L., Tella, A.

“…These locations have high industries and are well urbanized. The four machine learning algorithms exhibit high predictive performances, generally ascertaining the predictive accuracy of the climatic variables. …”
Get full text
Get full text

Modelling and investigating the impacts of climatic variables on ozone concentration in Malaysia using correlation analysis with random forest, decision tree regression, linear reg... by Balogun, A.-L., Tella, A.

“…These locations have high industries and are well urbanized. The four machine learning algorithms exhibit high predictive performances, generally ascertaining the predictive accuracy of the climatic variables. …”
Get full text
Get full text

MCMAC–CVT: a novel on-line associative memory based CVT transmission control system by Kai, Keng Ang, Quek, Chai, Abdul Rahman, Abdul Wahab

“…Engng, 10 (1996) 135) with momentum, neighborhood learning and Averaged Trapezoidal Output (MCMAC-ATO) as the neural control algorithm for controlling the CVT. …”
Get full text
Get full text
Get full text