Search Results - (( developing function machine algorithm ) OR ( learning application optimized algorithm ))

Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms by Hossain S.K.S., Ali S.S., Rushd S., Ayodele B.V., Cheng C.K.

Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems by Salih, Dhiadeen Mohammed

“…Wavelet networks (WNs) have been introduced as an alternative method of the neural networks for nonlinear system identification and used with model predictive control (MPC) techniques in many applications. Recently, an online sequential extreme learning machine (OSELM) algorithm has been introduced based on extreme learning machine (ELM) theories for single hidden layer feedforward neural networks (SLFN) and has been applied for different online applications. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…An efficient iterative algorithm is developed to optimize the objective function of the proposed algorithm since it is non-smooth and difficult to solve. …”
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Fault classification in smart distribution network using support vector machine by Chuan O.W., Ab Aziz N.F., Yasin Z.M., Salim N.A., Wahab N.A.

“…In this paper, a machine-learning algorithm known as Support Vector Machine (SVM) for fault type classification in distribution system has been developed. …”

Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee by Chong , Hue Yee

“…In this research work, the motivation is to develop an autonomous learning model based on the hybridization of an adaptive ANN and a metaheuristic algorithm for optimizing ANN parameters so that the network could perform learning and adaptation in a more flexible way and handle condition classification tasks more accurately in industries, such as in power systems. …”
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The predictive machine learning model of a hydrated inverse vulcanized copolymer for effective mercury sequestration from wastewater by Ghumman, A.S.M., Shamsuddin, R., Abbasi, A., Ahmad, M., Yoshida, Y., Sami, A., Almohamadi, H.

“…A predictive machine learning model was also developed to predict the amount of mercury removed () using GPR, ANN, Decision Tree, and SVM algorithms. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…The dissertation aims to develop an effectively decomposed time-series nongradient- based artificial intelligence model for forecasting a time-series regression machine learning task. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

Implementation of machine learning techniques with big data and IoT to create effective prediction models for health informatics by Zamani, Abu Sarwar, Hassan Abdalla Hashim, Aisha, Shatat, Abdallah Saleh Ali, Akhtar, Md. Mobin, Rizwanullah, Mohammed, Mohamed, Sara Saadeldeen Ibrahim

“…In the reduction phase, the optimal features are selected with theaid of the developed Hybrid Flower Pollination Bumblebees Optimization Algorithm (HFPBOA). …”
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Machine learning application in predicting anterior cruciate ligament injury among basketball players by Longfei, Guo

“…A one-year follow-up was conducted to monitor ACL injury, identifying n=11 injured players. Four machine learning algorithms—Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Logistic Regression (LR)—were developed to predict ACL injury. …”
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Training of interval type-2 fuzzy logic system using extreme learning machine for load forecasting by Hassan, S., Khosravi, A., Jaafar, J.

“…Extreme learning machine (ELM) is originally proposed for single- hidden layer feed-forward neural networks (SLFN). …”
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Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

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Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei by Chen , Shilei

“…By integrating ISMA, both supervised and unsupervised machine learning algorithms were investigated to develop real-time damage identification schemes. …”
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Development of a Neural-Fuzzy Model for Machinability Data Selection in Turning Process by Kong, Hong Shim

“…A neural-fuzzy model has been developed to represent machinability data selection in turning process. …”
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Sales prediction for Adha Station by using predictive analytics by Mohd Mokhid, Muhammad Amier Latieff

“…This research presented a technique for projecting sales utilising current data through a machine learning algorithm. The CRISP-DM approach was employed to execute the project across the phases of business understanding, data preparation, modelling, assessment, and deployment. …”
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Modular deep neural network in reducing overfitting to enhance generalization / Mohd Razif Shamsuddin by Shamsuddin, Mohd Razif

“…Machine Learning (ML) and Artificial Intelligence (AI) are a hype in this new age. …”
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A Modified Conjugate Gradient Method With Taylor Approximation: Applications In Electric Circuits And Image Restoration by Ahmad Alhawarat, Sultanah Masmali, Ibtisam Masmali, Mehiddin Al-Baali, Shahrina Ismail

Development of compound clustering techniques using hybrid soft-computing algorithms by Salim, Naomie, Shamsuddin, Siti Mariyam, Salleh @ Sallehuddin, Roselina, Alwee, Razana

“…The feed forward and radial basis functions networks show higher learning capabilities than support vector machines and rough set classifier in the classification of datasets comprising more than two classes. …”
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Stream-flow forecasting using extreme learning machines: A case study in a semi-arid region in Iraq by Yaseen, Z.M., Jaafar, O., Deo, R.C., Kisi, O., Adamowski, J., Quilty, J., El-Shafie, A.

“…The motivation for exploring and developing expert predictive models is an ongoing endeavor for hydrological applications. …”
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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.

“…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. …”