Intelligent sales prediction using machine learning techniques

S Cheriyan, S Ibrahim, S Mohanan… - 2018 International …, 2018‏ - ieeexplore.ieee.org
Intelligent Decision Analytical System requires integration of decision analysis and
predictions. Most of the business organizations heavily depend on a knowledge base and …

[كتاب][B] Particle swarm optimisation: classical and quantum perspectives

J Sun, CH Lai, XJ Wu - 2016‏ - books.google.com
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 …

A novel data clustering algorithm based on gravity center methodology

FH Kuwil, Ü Atila, R Abu-Issa, F Murtagh - Expert Systems with Applications, 2020‏ - Elsevier
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 …

Ant-based sorting and ACO-based clustering approaches: A review

AM Jabbar, KR Ku-Mahamud… - 2018 IEEE Symposium …, 2018‏ - ieeexplore.ieee.org
Data clustering is used in a number of fields including statistics, bioinformatics, machine
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

SE Comert, HR Yazgan, S Kır… - International Journal of …, 2018‏ - inderscienceonline.com
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 …

Automatic deep sparse multi-trial vector-based differential evolution clustering with manifold learning and incremental technique

P Hadikhani, DTC Lai, WH Ong… - Image and Vision …, 2023‏ - Elsevier
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 …

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 …

Fuzzy ants as a clustering concept

PM Kanade, LO Hall - … Conference of the North American Fuzzy …, 2003‏ - ieeexplore.ieee.org
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 …

A new data clustering algorithm based on critical distance methodology

FH Kuwil, F Shaar, AE Topcu, F Murtagh - Expert Systems with Applications, 2019‏ - Elsevier
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 …

Constrained ant colony optimization for data clustering

SC Chu, JF Roddick, CJ Su, JS Pan - … , New Zealand, August 9-13, 2004 …, 2004‏ - Springer
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 …