A hybrid approach of gravitational search algorithm and ant miner plus for fingerprint recognition

Article Computer Science, Interdisciplinary Applications

Hybrid big bang-big crunch with ant colony optimization for email spam detection

Rathika Natarajan et al.

Summary: This paper proposes a self-adaptive hybrid algorithm of big bang-big crunch (BB-BC) with ant colony optimization (ACO) for email spam detection, and it demonstrates its superiority over other techniques through experiments.

INTERNATIONAL JOURNAL OF MODERN PHYSICS C (2022)

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Article Computer Science, Interdisciplinary Applications

Intelligent gravitational search random forest algorithm for fake news detection

Rathika Natarajan et al.

Summary: The rise of online social media has changed the way people access news, but evaluating the reliability of news on social media becomes challenging due to its rapid rotation. To detect fake news, this paper proposes an intelligent gravitational search random forest algorithm that combines the intelligent gravitational search algorithm and the random forest algorithm. The algorithm generates decision trees to determine solutions and uses random proportional rules to generate a collection of solutions. The comprehensive prediction of news class (fake or real) is determined based on the attributes of random forest.

INTERNATIONAL JOURNAL OF MODERN PHYSICS C (2022)

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Article Computer Science, Interdisciplinary Applications

A novel hybrid approach of gravitational search algorithm and decision tree for twitter spammer detection

Luis Vives et al.

Summary: This paper proposes a novel approach for detecting Twitter spammers by combining the gravitational search algorithm and decision tree. The proposed method effectively addresses the challenges in spammer detection and outperforms other machine learning methods in experiments.

INTERNATIONAL JOURNAL OF MODERN PHYSICS C (2022)

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Article Computer Science, Interdisciplinary Applications

Quantum-inspired meta-heuristic algorithms with deep learning for facial expression recognition under varying yaw angles

Abhishek Bhatt et al.

Summary: In recent years, there has been a growing interest among researchers in facial expression recognition for accurately depicting human expressive changes resulting from increased human-computer interaction. This work utilizes the Local Binary Pattern and Histogram of Gradient techniques for facial feature extraction and optimizes them using quantum-inspired meta-heuristic algorithms. The results show that the optimized features, combined with deep learning techniques, improve the classification of facial expressions.

INTERNATIONAL JOURNAL OF MODERN PHYSICS C (2022)

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Article Computer Science, Interdisciplinary Applications

Quantum-inspired firefly algorithm integrated with cuckoo search for optimal path planning

Harish Kundra et al.

Summary: The study introduces an integrated quantum-inspired firefly algorithm with cuckoo search (IQFACS) for optimizing solution sets, showing promising results in path planning and optimization problems.

INTERNATIONAL JOURNAL OF MODERN PHYSICS C (2022)

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Article Computer Science, Interdisciplinary Applications

A novel quantum-behaved binary firefly algorithm with gravitational search algorithm to optimize the features for human activity recognition

Sonika Jindal et al.

Summary: This paper proposes a novel optimization approach called QBFA-GSA for discrete feature optimization using the quantum-behaved binary firefly algorithm and gravitational search algorithm, which is applied to human activity recognition. The experimental results show that the proposed approach performs superiorly and can effectively optimize features.

INTERNATIONAL JOURNAL OF MODERN PHYSICS C (2022)

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Article Mathematics

Automatic Fingerprint Classification Using Deep Learning Technology (DeepFKTNet)

Fahman Saeed et al.

Summary: Fingerprint recognition systems often face the challenge of high processing complexity, especially when multiple sensors are used. In this study, a technique for automatically determining the architecture of a CNN model adaptive to fingerprint classification was proposed, which effectively helps design lightweight models and enhances the speed of the recognition process. The method was evaluated using benchmark datasets and outperformed existing models and techniques.

MATHEMATICS (2022)

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Article Computer Science, Interdisciplinary Applications

An ensemble approach of improved quantum inspired gravitational search algorithm and hybrid deep neural networks for computational optimization

Yogesh Kumar et al.

Summary: This paper proposes an autonomous ensemble approach using an improved quantum inspired gravitational search algorithm and a hybrid deep neural network for optimizing computational problems. The method demonstrates superior recognition rate in facial expression recognition applications.

INTERNATIONAL JOURNAL OF MODERN PHYSICS C (2021)

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Article Computer Science, Interdisciplinary Applications

Deep neural networks-based classification optimization by reducing the feature dimensionality with the variants of gravitational search algorithm

Asha

Summary: The paper proposes a method to optimize features and improve system classification by amalgamating different concepts and combining deep neural network models with variants of the gravitational search algorithm. The experimental results show that the FDGSA technique with EDCNN has superior recognition accuracy.

INTERNATIONAL JOURNAL OF MODERN PHYSICS C (2021)

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Article Computer Science, Artificial Intelligence