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Start Over Author "Ahmad, Waleed" Publisher springer international publishing
20 results on '"Ahmad, Waleed"'

2. The Impact of Strategic Human Resources Management Practices on Firm Performance: The Mediating Role of Supply Chain Management

Author

Ahmad, Waleed, Zaid, Ahmed, Sleimi, Mohammad, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Alareeni, Bahaaeddin, editor, and Hamdan, Allam, editor

Published
2023
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6. Classification of Arrhythmia Using Machine Learning Techniques

Author

Saboori, Raisa, Salehi, Ahmad Waleed, Vaidya, Pankaj, Gupta, Gaurav, Pisello, Anna Laura, Editorial Board Member, Hawkes, Dean, Editorial Board Member, Bougdah, Hocine, Editorial Board Member, Rosso, Federica, Editorial Board Member, Abdalla, Hassan, Editorial Board Member, Boemi, Sofia-Natalia, Editorial Board Member, Mohareb, Nabil, Editorial Board Member, Mesbah Elkaffas, Saleh, Editorial Board Member, Bozonnet, Emmanuel, Editorial Board Member, Pignatta, Gloria, Editorial Board Member, Mahgoub, Yasser, Editorial Board Member, De Bonis, Luciano, Editorial Board Member, Kostopoulou, Stella, Editorial Board Member, Pradhan, Biswajeet, Editorial Board Member, Abdul Mannan, Md., Editorial Board Member, Alalouch, Chaham, Editorial Board Member, O. Gawad, Iman, Editorial Board Member, Nayyar, Anand, Editorial Board Member, Amer, Mourad, Series Editor, Singh, Pradeep Kumar, editor, Polkowski, Zdzislaw, editor, Tanwar, Sudeep, editor, Pandey, Sunil Kumar, editor, Matei, Gheorghe, editor, and Pirvu, Daniela, editor

Published
2021
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7. Multiple Machine Learning Models for Detection of Alzheimer’s Disease Using OASIS Dataset

Author

Baglat, Preety, Salehi, Ahmad Waleed, Gupta, Ankit, Gupta, Gaurav, Rannenberg, Kai, Editor-in-Chief, Soares Barbosa, Luís, Editorial Board Member, Goedicke, Michael, Editorial Board Member, Tatnall, Arthur, Editorial Board Member, Neuhold, Erich J., Editorial Board Member, Stiller, Burkhard, Editorial Board Member, Tröltzsch, Fredi, Editorial Board Member, Pries-Heje, Jan, Editorial Board Member, Kreps, David, Editorial Board Member, Reis, Ricardo, Editorial Board Member, Furnell, Steven, Editorial Board Member, Mercier-Laurent, Eunika, Editorial Board Member, Winckler, Marco, Editorial Board Member, Malaka, Rainer, Editorial Board Member, Sharma, Sujeet K., editor, Dwivedi, Yogesh K., editor, Metri, Bhimaraya, editor, and Rana, Nripendra P., editor

Published
2020
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8. A New Memory Updation Heuristic Scheme for Energy Management System in Smart Grid

Author

Ahmad, Waleed, Javaid, Nadeem, Khan, Sajjad, Zuraiz, Maria, Awan, Tayyab, Amir, Muhammad, Abbasi, Raza Abid, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Barolli, Leonard, editor, Takizawa, Makoto, editor, Xhafa, Fatos, editor, and Enokido, Tomoya, editor

Published
2020
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9. On Maximizing User Comfort Using a Novel Meta-Heuristic Technique in Smart Home

Author

Khan, Sajjad, Khan, Zahoor Ali, Javaid, Nadeem, Ahmad, Waleed, Abbasi, Raza Abid, Faisal, Hafiz Muhammad, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Barolli, Leonard, editor, Takizawa, Makoto, editor, Xhafa, Fatos, editor, and Enokido, Tomoya, editor

Published
2020
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10. Pro Utility Pro Consumer Comfort Demand Side Management in Smart Grid

Author

Ahmad, Waleed, Javaid, Nadeem, Karim, Basit, Jan, Syed Qasim, Ali, Muhammad, Abbasi, Raza Abid, Khan, Sajjad, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Barolli, Leonard, editor, Takizawa, Makoto, editor, Xhafa, Fatos, editor, and Enokido, Tomoya, editor

Published
2019
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11. Electricity Price Forecasting in Smart Grid: A Novel E-CNN Model

Author

Ahmad, Waleed, Javaid, Nadeem, Chand, Annas, Shah, Syed Yousaf Raza, Yasin, Umar, Khan, Mudassar, Syeda, Aimal, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Barolli, Leonard, editor, Takizawa, Makoto, editor, Xhafa, Fatos, editor, and Enokido, Tomoya, editor

Published
2019
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12. Minimizing Daily Cost and Maximizing User Comfort Using a New Metaheuristic Technique

Author

Abbasi, Raza Abid, Javaid, Nadeem, Khan, Sajjad, ur Rehman, Shujat, Amanullah, Asif, Rana Muhammad, Ahmad, Waleed, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Barolli, Leonard, editor, Takizawa, Makoto, editor, Xhafa, Fatos, editor, and Enokido, Tomoya, editor

Published
2019
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18. COVID-19: Automated Detection and Monitoring of Patients Worldwide Using Machine Learning

Author

Brij Bhushan Sharma, Ahmad Waleed Salehi, Gaurav Gupta, Sonia, Pankaj Vaidya, and Nagesh Kumar

Subjects
Coronavirus disease 2019 (COVID-19), Computer science, business.industry, Deep learning, Machine learning, computer.software_genre, Convolutional neural network, Test (assessment), Clinical prognosis, Artificial intelligence, Architecture, business, License, computer, Predictive modelling
Abstract

Novel COVID-19 or commonly known as Corona-Virus epidemic which was identified in Nov–Dec 2019, needs special consideration due to its future outbreaks and a possible threat to the world. Ever since, apart from clinical prognosis and diagnosis, AI (Artificial Intelligence) provides a novel paradigm for health-care, ML (Machine Learning) algorithms are employed in evaluating data and decision making processes. This means that AI–ML driven models help in identifying COVID-19 epidemic as well as predict their nature of spread across the world. Unlikely other health-care issues, for Corona-virus or COVID-19, for its detection, AI/ML-driven prediction models are anticipated to work as cross-population train and test models are the main perseverance of this chapter. The objective of this chapter is to know the novel COVID-19 epidemiology, its major prevention from spreading, and to assess the machine/deep learning-based architecture performance that is proposed in the present year for classification of COVID-19 images such as, X-Ray and CT. Especially, deep-learning centered algorithms known as the Convolutional Neural Network, which plays an excessive effect on mining highly essential features, mostly in terms of medical images. The performance of the technique is shown to be impressive with X-Ray and CT image scans, has been adopted in most of the recently published articles on the COVID-19/Coronavirus with notable results. Also, according to this chapter, that machine learning, as well as deep learning technology, has prospective clinical solicitations. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Published
2021

19. Classification of Arrhythmia Using Machine Learning Techniques

Author

Gaurav Gupta, Pankaj Vaidya, Ahmad Waleed Salehi, and Raisa Saboori

Subjects
Heartbeat, Heart disease, business.industry, Computer science, Disease, Machine learning, computer.software_genre, medicine.disease, U healthcare, Health problems, medicine, Artificial intelligence, Abnormality, Ecg signal, business, computer, Normal heart
Abstract

Arrhythmia and heart problems are one of the most important health problems in the whole world which leads to various other severe complications, for example, heart attack. As arrhythmia is a type of cardiologic disease, it can be used for pointing out the abnormality from normal heart activity and try to understand about heartbeat whether the heartbeat is normal or not. The main element that only a less number of people informed being discovered as a result of screening indicates that there are missing opportunities to prevent heart disease. There are different methods present for heart. Heart diseases are recognized by capturing information from patient’s body and forward results to doctors to reduce the risk of heart attack. So, the researcher always keeps trying to find out the best solution for this problem. The researchers have done huge research on this area, so according to the comparison between various techniques which are used for classification of arrhythmia, they prefer to use machine learning algorithm to achieve high performance and better accuracy.

Published
2021

20. Multiple Machine Learning Models for Detection of Alzheimer’s Disease Using OASIS Dataset

Author

Ahmad Waleed Salehi, Gaurav Gupta, Preety Baglat, and Ankit Gupta

Subjects
Activities of daily living, Computer science, business.industry, Decision tree, Disease, Logistic regression, medicine.disease, Machine learning, computer.software_genre, Random forest, Support vector machine, medicine, Dementia, AdaBoost, Artificial intelligence, business, computer
Abstract

Alzheimer’s Disease (AD) is the most common form of dementia that can lead to a neurological brain disorder that causes progressive memory loss as a result of damaging the brain cells and the ability to perform daily activities. This disease is one of kind and fatal. Early detection of AD because of its progressive threat and patients all around the world. The early detection is promising as it can help to predetermine the condition of lot of patients they might face in the future. So, by examining the consequences of the disease, using MRI images we can get the help of Artificial intelligence (AI) technology to classify the AD patients if they have or may not have the deadly disease in future. In recent years, AI-based Machine Learning (ML) techniques are very useful for the diagnosis of AD. In this paper, we have applied different machine learning techniques such as Logistic Regression, Decision Tree, Random forest classifier, Support Vector Machine and AdaBoost for the earlier diagnosis and classification of Alzheimer’s disease using Open Access Series of Imaging Studies (OASIS) dataset, in which a significant performance and result gained on classification with Random Forest classifier.

Published
2020

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