Search Results - (( evolution classification issues algorithm ) OR ( variable optimization means algorithm ))
Search alternatives:
- evolution classification »
- classification issues »
- variable optimization »
- optimization means »
- issues algorithm »
- means algorithm »
-
1
Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
Get full text
Get full text
Get full text
Get full text
Thesis -
2
Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
Get full text
Get full text
Thesis -
3
-
4
Identification of continuous-time hammerstein model using improved archimedes optimization algorithm
Published 2024“…Consequently, the proposed algorithm reliably determined the most optimal design variables during numerical trials, demonstrating 54.74% mean fitness function and 75.34% variable deviation indices enchantments compared to the traditional AOA. …”
Get full text
Get full text
Get full text
Get full text
Article -
5
Differential evolution for neural networks learning enhancement
Published 2008“…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
Get full text
Get full text
Get full text
Thesis -
6
A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…The results show that the neural network optimized with genetic algorithm and trained with an optimally and intelligently selected input vector containing historical load and meteorological variables produced the best prediction accuracy. …”
Get full text
Get full text
Article -
7
Email spam classification based on deep learning methods: A review
Published 2025“…Deep learning has become a potent collection of techniques for addressing intricate issues such as spam classification in recent times. …”
Get full text
Get full text
Get full text
Get full text
Article -
8
ENGINEERING DESIGN WITH PSO ALGORITHM
Published 2019“…This creates such problems and one of the root causes is the amount variables used by design engineers. To optimise a mechanical design by the means of distance or even shape, it needs to these handle large numbers of variables, and optimal solution is needed to for such systems. …”
Get full text
Get full text
Final Year Project -
9
-
10
A MODIFIED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR WELLBORE TRAJECTORY DESIGN
Published 2021“…To address this issue, a new hybridization of cellular automata (CA) technique with grey wolf optimization (GWO) and particle swarm optimization (PSO) algorithms is proposed in this work which solves these three optimization objectives of drilling through 17 tuning variables. …”
Get full text
Get full text
Thesis -
11
-
12
Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms
Published 2025“…Therefore, it is recommended to utilize the prediction algorithms within the range of input variables employed in this investigation for optimal results. ? …”
Article -
13
A Comparative Study Of Fuzzy C-Means And K-Means Clustering Techniques
Published 2014“…Next, we also optimize the fuzzification variable, m in FCM algorithm in order to improve the clustering performance. …”
Get full text
Get full text
Get full text
Conference or Workshop Item -
14
The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction
Published 2023“…This paper proposes an optimization algorithm based on the Binary Bat algorithm methodology for replacing the conventional orthogonal array approach. …”
Article -
15
Development of genetic algorithm for optimization of yield models in oil palm production
Published 2018“…Moreover, models were built on the basis of variables that have been selected by the GA. Across the optimization, procedures obtained the best Two Factor Interaction (2FI) models to achieve the best model of oil palm productivity prediction with a value of R2 of 0.948, mean squared error of 0.022, and the model P-value of < 0.0001 in Sabah. …”
Get full text
Get full text
Get full text
Article -
16
Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management
Published 2024“…Evaluation metrics such as Mean Squared Error, Root Mean Squared Error, Mean Absolute Error, and R-squared are commonly employed in the assessment of Machine Learning models' performance. …”
Get full text
Get full text
Article -
17
Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
Get full text
Get full text
Thesis -
18
-
19
Seed disperser ant algorithm for optimization / Chang Wen Liang
Published 2018“…In this research, we applied SDAA to solve the constrained engineering problems and introduce an efficient data clustering algorithm which is hybrid of K-means and SDAA. The optimal results obtained for constrained engineering problems as well as data clustering are very promising in terms of quality of solutions and convergence speed of the algorithm.…”
Get full text
Get full text
Get full text
Thesis -
20