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Intelligent sales prediction using machine learning techniques
Intelligent Decision Analytical System requires integration of decision analysis and
predictions. Most of the business organizations heavily depend on a knowledge base and …
predictions. Most of the business organizations heavily depend on a knowledge base and …
[كتاب][B] Particle swarm optimisation: classical and quantum perspectives
Although the particle swarm optimisation (PSO) algorithm requires relatively few parameters
and is computationally simple and easy to implement, it is not a globally convergent …
and is computationally simple and easy to implement, it is not a globally convergent …
A novel data clustering algorithm based on gravity center methodology
The concept of clustering is to separate clusters based on the similarity which is greater
within cluster than among clusters. The similarity consists of two principles, namely …
within cluster than among clusters. The similarity consists of two principles, namely …
Ant-based sorting and ACO-based clustering approaches: A review
Data clustering is used in a number of fields including statistics, bioinformatics, machine
learning exploratory data analysis, image segmentation, security, medical image analysis …
learning exploratory data analysis, image segmentation, security, medical image analysis …
A cluster first-route second approach for a capacitated vehicle routing problem: a case study
In this study, a capacitated vehicle routing problem (CVRP) which dealt with minimum
distance routes for vehicles that serve customers having specific demands from a common …
distance routes for vehicles that serve customers having specific demands from a common …
Automatic deep sparse multi-trial vector-based differential evolution clustering with manifold learning and incremental technique
Most deep clustering methods despite utilizing complex networks to learn better from data,
use a shallow clustering method. These methods have difficulty in finding good clusters due …
use a shallow clustering method. These methods have difficulty in finding good clusters due …
Association clustering and time series based data mining in continuous data for diabetes prediction
S Rani, S Kautish - 2018 second international conference on …, 2018 - ieeexplore.ieee.org
Large amount of health related data is being produced in various levels of health system.
Due to the size of the data it will be difficult to process the data and then extract the analysis …
Due to the size of the data it will be difficult to process the data and then extract the analysis …
Fuzzy ants as a clustering concept
We present a swarm intelligence approach to data clustering. Data is clustered without initial
knowledge of the number of clusters. Ant based clustering is used to initially create raw …
knowledge of the number of clusters. Ant based clustering is used to initially create raw …
A new data clustering algorithm based on critical distance methodology
A variety of algorithms have recently emerged in the field of cluster analysis. Consequently,
based on the distribution nature of the data, an appropriate algorithm can be chosen for the …
based on the distribution nature of the data, an appropriate algorithm can be chosen for the …
Constrained ant colony optimization for data clustering
Processes that simulate natural phenomena have successfully been applied to a number of
problems for which no simple mathematical solution is known or is practicable. Such meta …
problems for which no simple mathematical solution is known or is practicable. Such meta …