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1
Optimized clustering with modified K-means algorithm
Published 2021“…Empirical evidences based on simulated data sets indicated that the proposed modified k-means algorithm is able to recognise the optimum number of clusters for uncorrelated data sets. …”
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Thesis -
2
New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems
Published 2024“…However, the complexity significantly rises when dealing with multi objective functions. The Modified Adaptive Bats Sonar Algorithm (MABSA), initially designed for single objective optimization and inspired by colony bats' echolocation, has demonstrated efficiency with its simple structure and reduced computation time. …”
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3
Whale optimization algorithm strategies for higher interaction strength t-way testing
Published 2022“…To ensure that WOA conquers premature convergence and avoids local optima for large search spaces (owing to high-order interaction), three variants of WOA have been developed, namely Structurally Modified Whale Optimization Algorithm (SWOA), Tolerance Whale Optimization Algorithm (TWOA), and Tolerance Structurally Modified Whale Optimization Algorithm (TSWOA). …”
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4
Modified ACS centroid memory for data clustering
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5
Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems
Published 2023“…It is an iterative algorithm with descent properties that reduces computational cost by using derivatives of random data points. …”
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6
An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion
Published 2018“…We have chosen four neighborhood based algorithms which are commonly used in optimization problems and divided them in newly implemented and re-implemented category. …”
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7
An ensemble of neural network and modified grey wolf optimizer for stock prediction
Published 2019“…Additionally, the research restricts the number of variables through feature selection to enhance the performance of the algorithm. Subsequently, the research attempts to construct an ensemble model applying Modified Grey Wolf Optimizer (MGWO) and neural network for stock prediction. …”
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8
Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models
Published 2024“…This study proposes ensemble models for predicting LDC based on multilayer perceptron (MULP) methods and optimization algorithms. The honey badger optimization algorithm (HBOA), salp swarm algorithm (SASA), firefly algorithm (FIFA), and particle swarm optimization algorithm (PASOA) are used to adjust the MULP parameters. …”
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9
The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification
Published 2020“…Technically, BFOA has been applied as supplementary algorithm for optimizing weight, parameters for other classifier algorithms and selecting optimised features for other classifiers. …”
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10
BASE: a bacteria foraging algorithm for cell formation with sequence data
Published 2010“…In addition, a newly developed BFA-based optimization algorithm for CF based on operation sequences is discussed. …”
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11
Balancing exploration and exploitation in ACS algorithms for data clustering
Published 2019“…Ant colony optimization (ACO) is a swarm algorithm inspired by different behaviors of ants. …”
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12
Optimizing decentralized exam timetabling with a discrete whale optimization algorithm
Published 2025“…—In recent years, there has been increasing interest in intelligent optimization algorithms, such as the Whale Optimization Algorithm (WOA). …”
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13
Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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14
Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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15
Resource allocation technique for powerline network using a modified shuffled frog-leaping algorithm
Published 2018“…Finally, joint allocation models for selection of optima resource values are introduced; adaptive power and bit allocators in OFDM system-based Powerline and using modified SFLA-based TLBO and PSO are proposed…”
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Thesis -
16
Modified word representation vector based scalar weight for contextual text classification
Published 2024“…Overall, this thesis presents five contributions: the proposed modified word vectors algorithm, the new contextual classification dataset named QCoC, the efficient question-type classifier based on the feed-forward neural network algorithm, the potential transferability of the presented work to other domains, and the practical implications of the presented work towards cases where computational resources are limited or costly.…”
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17
Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…Despite attempts to solve the data clustering issues, there are also many variants of modified algorithms in traditional information clustering that attempt to solve issues such as clustering algorithms based on condensation. …”
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18
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 -
19
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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20
Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm
Published 2025“…In recent years, there has been increasing interest in intelligent optimization algorithms, such as the Whale Optimization Algorithm (WOA). …”
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