LANDSLIDE SUSCEPTIBILITY PREDICTION MODELING BASED ON REMOTE SENSING AND A NOVEL DEEP LEARNING ALGORITHM OF A CASCADE-PARALLEL RECURRENT NEURAL NETWORK

Landslide susceptibility prediction (LSP) modeling is an important and challenging problem.Landslide features are generally uncorrelated or nonlinearly correlated, resulting in limited LSP performance when leveraging conventional machine learning models.In this study, a deep-learning-based model using the long short-term memory (LSTM) recurrent neu

Matthias W Riepe Mental Health and Geriatric Psychiatry, Psychiatry II, Ulm University, Ulm, Germany Abstract: Little is known about symptom preferences of clinical psychiatrists in the treatment of geriatric depression and preferences for avoiding adverse drug effects.Participants (board-certified psychiatrists) were recruited prior to a lect

The article defines the importance of patriotic education of the modern generation of youth.The need for the formation of patriotism among students studying in the defense specialties of universities, which is distinguished by an orientation towards the specifics of future professional activity, axon fixed blade defined as professionally oriented p