1. Arthur, C. K., Bhatawdekar, R. M., Temeng, V. A., Agyei, G. and Ziggah, Y. Y.(2024), Application of artificial intelligence in predicting blast-induced ground vibration In: Applications of Artificial Intelligence in Mining, Geotechnical and Geoengineering, pp. 251-267.
2. Brantson, E. T., Iyiola, Z. O., Ziggah, Y. Y., Mensah, A. O., Otchere, D. A., Abakah-Paintsil, E. E. and Duodu, E. K.(2023), Carbon Dioxide Low Salinity Water Alternating Gas (CO2 LSWAG) Oil Recovery Factor Prediction in Carbonate Reservoir Using Supervised Machine Learning Models In: Data Science and Machine Learning Applications in Subsurface Engineering, pp. 1-34.
3. Ofori-Ntow E. J, Ziggah, Y. Y., Rahmani-Andebili, M., Rodrigues, M. J. and Relvas, S. (2022), A Novel Three Stage Short-Term Photovoltaic Prediction Approach Based on Neighbourhood Component Analysis and ANN Optimized with PSO (NCA-PSO-ANN) In: Rahmani-Andebili, M. (eds) Applications of Artificial Intelligence in Planning and Operation of Smart Grids, Power Systems, Springer, Cham, pp. 75-95.
4. Yao Yevenyo Ziggah, Hu Youjian, Xiao Benlin (2013), Determination of GPS Coordinates Transformation Parameters: A Case Study of Ghana Geodetic Reference Network LAP LAMBERT Academic Publishing, Saarbrucken, Germany, ISBN-13 : 978-3659391156, pp. 1-296.