Hiroshi Yajima

Application of the Random Forest model for chlorophyll-a forecasts in fresh and brackish water bodies in Japan, using multivariate long-term databases

Hiroshi Yajima, Jonathan Derot · Journal of Hydroinformatics · 2017 · 111 citations

Environmental Monitoring, Engineering, Forest Hydrology +19

Application Of Neural Network To Technical Analysis Of Stock Market Prediction

Hirotaka Mizuno, Michitaka Kosaka, Hiroshi Yajima et al. · 2001 · 105 citations

Engineering, Machine Learning, Predictive Analytics +14

Advances in forecasting harmful algal blooms using machine learning models: A case study with Planktothrix rubescens in Lake Geneva

Jonathan Derot, Hiroshi Yajima, Stéphan Jacquet · Harmful Algae · 2020 · 73 citations · Full text

Environmental Monitoring, Engineering, Ecological Modelling +9

Evaluation of Unified Algorithms for Remote Sensing of Chlorophyll-a and Turbidity in Lake Shinji and Lake Nakaumi of Japan and the Vaal Dam Reservoir of South Africa under Eutrophic and Ultra-Turbid Conditions

Yuji Sakuno, Hiroshi Yajima, Yumi Yoshioka et al. · Water · 2018 · 33 citations · Full text

Environmental Monitoring, Engineering, Oceanography +16

Benefits of machine learning and sampling frequency on phytoplankton bloom forecasts in coastal areas

Jonathan Derot, Hiroshi Yajima, François G. Schmitt · Ecological Informatics · 2020 · 31 citations · Full text

Coastal Management, Ocean Monitoring, Environmental Monitoring +11