Search Results - (( using optimization model algorithm ) OR ( variable detection using algorithm ))

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

Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification by Abd Samad, Md Fahmi

“…A deterministic mutation-based algorithm is introduced to overcome this problem. Identification studies using NARX (Nonlinear AutoRegressive with eXogenous input) models employing simulated systems and real plant data are used to demonstrate that the algorithm is able to detect significant variables and terms faster and to select a simpler model structure than other well-known EC methods.…”
Get full text
Get full text
Get full text

Fault Detection Relevant, Neural Network and Evolutionary Algorithm based Model for a Single-shaft Industrial Gas Turbine by Alemu Lemma, Tamiru, Rangkuti, Chalillullah, Mohd Hashim, Fakhruldin

“…C. The model can also be used for performance optimization studies.…”
Get full text

Chemometrics analysis for the detection of dental caries via ultraviolet absorption spectroscopy / Katrul Nadia Basri by Basri, Katrul Nadia

“…The best performance obtained using Savitzky-Golay smoothing and LDA algorithms after the wavelength selection with the accuracy reported of 0.90. …”
Get full text
Get full text

An Optimized Semantic Segmentation Framework for Human Skin Detection by Huong, Audrey, Ngu, Xavier

“…Existing approaches used complex and various heuristic designs of image processing algorithms and deep models customized for skin detection problems. …”
Get full text
Get full text
Get full text

Non-weighted aggregate evaluation function of multi-objective optimization for knock engine modeling by Witwit, Azher Razzaq Hadi

“…The NWAEF model was compared to Random Weights Genetic Algorithm (RWGA) model by using five data sets taken from different internal combustion engines. …”
Get full text
Get full text
Get full text

A multi-nets ANN model for real-time performance-based automatic fault diagnosis of industrial gas turbine engines by Tahan, M., Muhammad, M., Abdul Karim, Z.A.

“…Two back-propagation training algorithms, namely the Levenberg–Marquardt and Bayesian regularization algorithms, and the k-fold cross-validation technique, were employed to train the optimal networks using a training data set. …”
Get full text
Get full text

Modelling of cupping suction system based on system identification method by Suresh, Kavindran, Ghazali, M. R., Ahmad, M. A.

“…The detection of cupped suction system plants using a standard model based on a modified Sine Cosine Algorithm (mSCA) is presented in this research. …”
Get full text
Get full text
Get full text
Get full text

New synchronization protocol for distributed system with TCP extension by Bayat, Peyman

“…The resulting algorithm does not involve variability in the hardware type nor is it based on specific distributed application software or databases. …”
Get full text
Get full text

Cross-domain analysis of YOLOv8 and faster R-CNN models for enhanced precision in maritime object detection by Zainal Abidin, Zulkifli, Norazaruddin, Muhammad Aiman, Tengku Anuar, Tengku Aizat

“…Overall, the findings emphasize the need to carefully select object detection algorithms tailored to dataset characteristics in order to optimize performance across diverse maritime environments.…”
Get full text
Get full text
Get full text
Get full text

A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping by Althuwaynee, Omar F., Pradhan, Biswajeet, Park, Hyuck Jin, Lee, Jung Hyun

“…An ensemble algorithm of data mining decision tree (DT)-based CHi-squared Automatic Interaction Detection (CHAID) is widely used for prediction analysis in variety of applications. …”
Get full text
Get full text

Power System State Estimation In Large-Scale Networks by NURSYARIZAL MOHD NOR, NURSYARIZAL

“…Hence. SE requires to use various techniques to ensure validity of the results and to detect and identify sources of errors. …”
Get full text
Get full text

Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration by Althuwaynee, Omar F., Pradhan, Biswajeet, Ahmad, Noordin

“…LR model was used to find the corresponding coefficients of best fitting function that assess the optimal terminal nodes. …”
Get full text
Get full text

Modeling of cupping suction system based on system identification method by Kavindran, Suresh

“…The input and output data were used to create this modeling output variable of the cupping suction system is detected by connecting a differential pressure sensor to the cup, while the input variable is determined by the speed of the pump applied in various locations. …”
Get full text
Get full text

Identification of debris flow initiation zones using topographic model and airborne laser scanning data by Lay, Usman Salihu, Pradhan, Biswajeet

“…Conditioning parameters were numerically optimized to identify the arbitrarily maximum model basis function for eleven variables, using MARSplines analysis (algorithm). …”
Get full text
Get full text
Get full text

Stochastic Modelling Of Bioethanol Fermentation By Saccharomyces Cerevisiae Grown In Oil Palm Residues by Samsudin , Mohd Dinie Muhaimin

“…However, this result might differ if it is to be reduplicated due to heterogeneity of OPT sap and POME as well as variability in Baker’s yeast’s performance. Therefore, a predictability test was carried out using Monte Carlo algorithm. …”
Get full text
Get full text

Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis by Adnani, Seyedeh Atena

“…In this system,similar insolvent system, three methods including one variable at a time, Taguchi method and ANN were used for optimization and prediction of percentage of conversion. …”
Get full text
Get full text

A hybrid chromaticity-morphological machine learning model to overcome the limit of detecting newcastle disease in experimentally infected chicken within 36 h by Bakar, Mohd Anif A.A., Ker, Pin Jern, Tang, Shirley G.H., Arman Shah, Fatin Nursyaza, Mahlia, T. M.Indra, Baharuddin, Mohd Zafri, Omar, Abdul Rahman

“…This work demonstrates a promising methodology in developing machine learning algorithm using hybrid chromaticity-morphological features for early detection of virus-infected chickens, contributing to the goal of a sustainable and healthier planet.…”
Get full text
Get full text
Get full text

An intelligent optical fibre Al(lll) sensor based on advanced materials-sol-gel & polyaniline-porous nanocomposite / Faiz Bukhari Mohd Suah, Abdul Mutalib Md Jani and Mohd Nasir Ta... by Mohd Suah, Faiz Bukhari, Md Jani, Abdul Mutalib, Taib, Mohd Nasir

“…An orthogonal design is utilized to design the experimental protocol, in which three variables are varied simultaneously. Feedforward-type neural networks with faster back propagation (BP) algorithm are applied to model the system, and then optimization of the experimental conditions is carried out in the neural network with 3:7:1 structure, which have been confirmed to be able to provide the maximum performance. …”
Get full text
Get full text

AI Adoption for Steam Boiler Trip Prevention in Thermal Power Plants by Ismail F.B., Al-Kayiem H.H., Kazem H.A.

“…The first intelligent system capitalizes on a pure Artificial Neural Network (ANN) approach, leveraging the insights drawn from plant operators' decision-making processes concerning the key variables influencing each specific boiler trip. On the other hand, the second system takes a hybrid approach, incorporating Genetic Algorithms (GAs) to emulate the decision-making role of plant operators in identifying the most influential variables for each trip. …”