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Mohammad H. Nadimi-Shahraki, Zahra Asghari Varzaneh, Hoda Zamani and Seyedali Mirjalili
Feature selection is an NP-hard problem to remove irrelevant and redundant features with no predictive information to increase the performance of machine learning algorithms. Many wrapper-based methods using metaheuristic algorithms have been proposed to...
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Mohammad Tubishat, Feras Al-Obeidat, Ali Safaa Sadiq and Seyedali Mirjalili
Spam emails have become a pervasive issue in recent years, as internet users receive increasing amounts of unwanted or fake emails. To combat this issue, automatic spam detection methods have been proposed, which aim to classify emails into spam and non-...
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Armin Razmjoo, Amirhossein Gandomi, Maral Mahlooji, Davide Astiaso Garcia, Seyedali Mirjalili, Alireza Rezvani, Sahar Ahmadzadeh and Saim Memon
As smart cities (SCs) emerge, the Internet of Things (IoT) is able to simplify more sophisticated and ubiquitous applications employed within these cities. In this regard, we investigate seven predominant sectors including the environment, public transpo...
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El-Sayed M. El-Kenawy, Nima Khodadadi, Ashin Khoshnaw, Seyedali Mirjalili, Amel Ali Alhussan, Doaa Sami Khafaga, Abdelhameed Ibrahim and Abdelaziz A. Abdelhamid
Recently, piracy and copyright violations of digital content have become major concerns as computer science has advanced. In order to prevent unauthorized usage of content, digital watermarking is usually employed. This work proposes a new approach to di...
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Shahriar Shakir Sumit, Dayang Rohaya Awang Rambli, Seyedali Mirjalili, Muhammad Mudassir Ejaz and M. Saef Ullah Miah
Human detection is a special application of object recognition and is considered one of the greatest challenges in computer vision. It is the starting point of a number of applications, including public safety and security surveillance around the world. ...
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Mohammad H. Nadimi-Shahraki, Mahdis Banaie-Dezfouli, Hoda Zamani, Shokooh Taghian and Seyedali Mirjalili
Advancements in medical technology have created numerous large datasets including many features. Usually, all captured features are not necessary, and there are redundant and irrelevant features, which reduce the performance of algorithms. To tackle this...
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Mohammad H. Nadimi-Shahraki, Ebrahim Moeini, Shokooh Taghian and Seyedali Mirjalili
In this paper, a discrete moth?flame optimization algorithm for community detection (DMFO-CD) is proposed. The representation of solution vectors, initialization, and movement strategy of the continuous moth?flame optimization are purposely adapted in DM...
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Qasem Al-Tashi, Emelia Akashah Patah Akhir, Said Jadid Abdulkadir, Seyedali Mirjalili, Tareq M. Shami, Hitham Alhusssian, Alawi Alqushaibi, Ayed Alwadain, Abdullateef O. Balogun and Nasser Al-Zidi
The accurate classification of reservoir recovery factor is dampened by irregularities such as noisy and high-dimensional features associated with the reservoir measurements or characterization. These irregularities, especially a larger number of feature...
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