Search Results - (( data optimization _ algorithm ) OR ( data normalization techniques algorithm ))
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price
Published 2014“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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Conference or Workshop Item -
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma
Published 2017“…In addition, the algorithm was relatively easy to understand compare to the state of the art of normal parameter reduction algorithm. …”
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Artificial neural network-salp-swarm algorithm for stock price prediction
Published 2024“…The results show that the SSA-ANN model outperforms other models when applied to normalized data. Additionally, the SSA-ANN model is compared with other two hybrid models: the ANN optimized by the Whale Optimization Algorithm (WOA-ANN) and Moth-Flame Optimizer (MOA-ANN), as well as a single model, namely the Autoregressive Integrated Moving Average (ARIMA). …”
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Article -
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Predicting bankruptcy using ant colony optimization / Nur Syafiqah Abdul Ghani
Published 2021“…Data pre-processing method carries out certain computations such as data transformation (normalization, aggregation) to improve data quality. …”
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Student Project -
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An efficient IDS using hybrid Magnetic swarm optimization in WANETs
Published 2018“…In order to improve the accuracy of artificial neural network (ANN) classifier, we have integrated our proposed hybrid magnetic optimization algorithm-particle swarm optimization (MOA-PSO) technique. …”
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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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Application of Evolutionary Algorithm for Assisted History Matching
Published 2014“…Today, tremendous efforts are made to develop Automatic History Matching algorithms. While the automatic method focus on optimization which is normally computer based. …”
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Final Year Project -
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An Efficient IDS Using Hybrid Magnetic Swarm Optimization in WANETs
Published 2018“…In order to improve the accuracy of artificial neural network (ANN) classifier, we have integrated our proposed hybrid magnetic optimization algorithm-particle swarm optimization (MOA-PSO) technique. …”
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Article -
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Optimal network reconfiguration and intelligent service restoration prediction technique based on Cuckoo search spring algorithm / Mohamad Izwan Zainal
Published 2022“…Later, this MOCSSA is applied on service restoration to ensure the proposed algorithm technique is suitable in selecting the optimal switches for supply recovery after the line section is isolated from the system either by forced outage or planned outage purposes. …”
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Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…We introduced two new approaches to normalization techniques to enhance the K-Means algorithms. …”
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Normalized Relational Storage for Extensible Markup Language (XML) Schema
Published 2011“…Approach: In this study we present an algorithm for generating an optimal design for XML in relational setting. …”
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Journal -
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A Comparative Study of Z-Score and Min-Max Normalization for Rainfall Classification in Pekanbaru
Published 2024“…The objective is to compare various data normalization techniques, including Min-Max Normalization and Z-Score Normalization. …”
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Logic Programming In Radial Basis Function Neural Networks
Published 2013“…I used different types of optimization algorithms to improve the performance of the neural networks. …”
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Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms
Published 2025“…This study presents a hybrid approach combining the CatBoost algorithm with metaheuristic optimization techniques to enhance SoC estimation accuracy and robustness. …”
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Article -
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Weather prediction in Kota Kinabalu using linear regressions with multiple variables
Published 2021“…The root mean square error is used to compare the performance of the algorithms. The findings showed that the normal equation technique anticipates the weather with a high degree of accuracy, but the gradient descent technique predicts the low degree of accuracy.…”
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Proceedings -
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The effect of pre-processing techniques and optimal parameters on BPNN for data classification
Published 2015“…The Min-Max, Z-Score, and Decimal Scaling Normalization pre-processing techniques were analyzed. …”
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Improved Genetic Algorithm Multilayer Perceptron Network For Data Classification
Published 2017“…The proposed technique avoids the destruction of nearly optimal information contained in the gene segment and allows offspring to inherit highly important information among multiple parents. …”
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