IPOC: an efficient approach for dynamic association rule generation using incremental data with updating supports

Naresh, P.; Suguna, R.

doi:10.11591/ijeecs.v24.i2.pp1084-1090

Cited by 9 publications

(2 citation statements)

References 30 publications

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“…-Infrequent patterns are not handled effectively IPOC [43] -Implements an efficient IPOC. A frequent item set generation algorithm was applied to this tree.…”

Section: Using Multiple Techniques Can Add To the Time Complexity Of ...mentioning

confidence: 99%

A genetic algorithm coupled with tree-based pruning for mining closed association rules

Poovan

Acharya

Reddy

2023

IJECE

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Due to the voluminous amount of itemsets that are generated, the association rules extracted from these itemsets contain redundancy, and designing an effective approach to address this issue is of paramount importance. Although multiple algorithms were proposed in recent years for mining closed association rules most of them underperform in terms of run time or memory. Another issue that remains challenging is the nature of the dataset. While some of the existing algorithms perform well on dense datasets others perform well on sparse datasets. This paper aims to handle these drawbacks by using a genetic algorithm for mining closed association rules. Recent studies have shown that genetic algorithms perform better than conventional algorithms due to their bitwise operations of crossover and mutation. Bitwise operations are predominantly faster than conventional approaches and bits consume lesser memory thereby improving the overall performance of the algorithm. To address the redundancy in the mined association rules a tree-based pruning algorithm has been designed here. This works on the principle of minimal antecedent and maximal consequent. Experiments have shown that the proposed approach works well on both dense and sparse datasets while surpassing existing techniques with regard to run time and memory.

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“…-Infrequent patterns are not handled effectively IPOC [43] -Implements an efficient IPOC. A frequent item set generation algorithm was applied to this tree.…”

Section: Using Multiple Techniques Can Add To the Time Complexity Of ...mentioning

confidence: 99%

A genetic algorithm coupled with tree-based pruning for mining closed association rules

Poovan

Acharya

Reddy

2023

IJECE

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“…In hypothetical scenarios, artificial neural network (ANN) models consist of interconnected neurones and weights. The researchers are utilising a highly interconnected system of processing factors to analyse complex relationships between dependent and independent variables [14]. Artificial neural networks (ANNs) are complex interconnected structures composed of numerous processing units known as neurones.…”

Section: Artificial Neural Network (Ann)mentioning

confidence: 99%

ANN and RSM based Modeling of Moringa Stenopetala Seed Oil Extraction: Process Optimization and Oil Characterization

Ravi,

Raghavendran,

Satish

et al. 2023

IJRITCC

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Moringa Stenopetala is a plant species that is endemic to the southern region of Ethiopia. It is primarily cultivated for its nutritional value and is considered an important food source. The present research aimed to analyse the physicochemical properties of Moringa Stenopetala seed oil (MSO) obtained through solvent extraction method utilising hexane as the solvent. The collection of seeds was conducted in Adama, which is situated in the East Shawa zone of Oromia, Ethiopia. Prior to the extraction procedure, the seeds' average moisture content, crude ash, fibre, protein, and oil content were analysed and found to be 6.27%, 7.8%, 2.7%, 26.5%, and 43.2%, respectively. Using the Response Surface Method (RSM) and Artificial Neural Network (ANN), the extraction process was modeled. The study utilised numerical solutions to determine the optimal process parameters for maximising oil yield during extraction. The results indicated that a particle size of 0.85mm, a temperature of 85°C, and an extraction time of 4.75 hours were the most effective parameters. Furthermore, an investigation was conducted on the physical and chemical properties of the oil obtained under optimised conditions.

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Deep Learning based Object Tracking and Detection for Autonomous Drones using YOLOv3

Leela,

Varun,

Uma

et al. 2024

2024 3rd International Conference on Applied Artificial Intelligence and Computing (ICAAIC)

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IPOC: an efficient approach for dynamic association rule generation using incremental data with updating supports

Cited by 9 publications

References 30 publications

A genetic algorithm coupled with tree-based pruning for mining closed association rules

A genetic algorithm coupled with tree-based pruning for mining closed association rules

ANN and RSM based Modeling of Moringa Stenopetala Seed Oil Extraction: Process Optimization and Oil Characterization

Deep Learning based Object Tracking and Detection for Autonomous Drones using YOLOv3

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