Search Results - (( based optimization based algorithm ) OR ( data normalization learning algorithm ))
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One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network
Published 2012“…Based on result obtained, it shows that IWO learning algorithm is capable to produce accurate prediction load demand. …”
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Student Project -
2
A new variant of black hole algorithm based on multi population and levy flight for clustering problem
Published 2020“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems. …”
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Thesis -
3
Flock optimization algorithm-based deep learning model for diabetic disease detection improvement
Published 2024“…Hence, the research objective is to create an improved diabetic disease detection system using a Flock Optimization Algorithm-Based Deep Learning Model (FOADLM) feature modeling approach that leverages the PIMA Indian dataset to predict and classify diabetic disease cases. …”
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Article -
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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Thesis -
5
Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…Classification of imbalanced datasets remained a significant issue in data mining and machine learning (ML) fields. This research work proposed a new idea based on the optimization for handling the imbalanced datasets. …”
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6
Weather prediction in Kota Kinabalu using linear regressions with multiple variables
Published 2021“…This study employs machine learning algorithms, a linear regression model using statistics, and two optimization approaches, the normal equation approach, and gradient descent approach to predict the weather based on a few variables. …”
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Proceedings -
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…The best algorithm will not be the same for all the data sets. …”
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Book Section -
8
Privacy optimization and intrusion detection in modbus/tcp network-based scada in water distribution systems
Published 2021“…Another problematic aspect is related to the intrusion detection solutions that are based on machine learning cluster algorithms to learn systems’ specifications and extract general state-based rules for attacks identification. …”
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Thesis -
9
Forecasting and Trading of the Stable Cryptocurrencies With Machine Learning and Deep Learning Algorithms for Market Conditions
Published 2023“…Thus, this proposed system employs a data science-based framework and six highly advanced data-driven Machine learning and Deep learning algorithms: Support Vector Regressor, Auto-Regressive Integrated Moving Average (ARIMA), Facebook Prophet, Unidirectional LSTM, Bidirectional LSTM, Stacked LSTM. …”
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Article -
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…The proposed method integrates colour and texture feature-based image analysis with machine learning algorithms for classification. …”
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Thesis -
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Performance evaluation of intrusion detection system using selected features and machine learning classifiers
Published 2021“…These evolutionary-based algorithms are known to be effective in solving optimization problems. …”
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Article -
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IoT-Enabled Waste Tracking and Recycling Optimization : Enhancing Sustainable Waste Management
Published 2025“…Advanced data preprocessing, such as augmentation and normalization, ensures robust model training, while optimized algorithms guide waste sorting based on classification results. …”
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Proceeding -
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Characterization of oil palm fruitlets using artificial neural network
Published 2014“…The results also showed that contrary to the widely reported gap between the accuracy of the LM algorithm and other feed forward neural network training algorithms, the RP trained network performed as good as that of the LM algorithm for the range of data considered. …”
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Deep learning-based item classification for retail automation
Published 2025“…This project focuses on developing a deep learning-based system for retail item classification. …”
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Final Year Project / Dissertation / Thesis -
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Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli
Published 2014“…The backpropagation algorithm is one of the most famous algorithms to train neural network based on the mean square error (MSE) of ordinary least squares (OLS). …”
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Book Section -
16
The effect of pre-processing techniques and optimal parameters on BPNN for data classification
Published 2015“…The architecture of artificial neural network (ANN) laid the foundation as a powerful technique in handling problems such as pattern recognition and data analysis. It’s data-driven, self-adaptive, and non-linear capabilities channel it for use in processing at high speed and ability to learn the solution to a problem from a set of examples. …”
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Hybrid neural network in medicolegal degree of injury determination based on Visum et Repertum
Published 2023“…Pre-processing phase overcomes the issue of incomplete data by performing data cleansing and data normalization. …”
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Predicting Market Trends : A Stock Prices Forecasting with Artificial Neural Network for Apple Inc. and Microsoft Corp.
Published 2025“…Consequently, numerous studies have explored the use of machine learning for stock price forecasting. Hence, this study employs an Artificial Neural Network model as a machine learning algorithm for forecasting stock prices. …”
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Article -
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Monotone Data Samples Do Not Always Produce Monotone Fuzzy If- Then Rules: Learning with Ad hoc and System Identification Methods
Published 2017“…The same observation can be made, empirically, using a system identification method, e.g., a derivative–based optimization method and the genetic algorithm. …”
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Article -
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Mean of correlation method for optimization of affective states detection in children
Published 2018“…With the requirement of having the measuring device attached to the body approach, distraction of the subject normally masks the true affective states of the subject due to discomfort. …”
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