Results 21 to 30 of about 1,496,086 (365)
Portfolio Optimization with Sparse Multivariate Modelling [PDF]
arXiv, 2021 Portfolio optimization approaches inevitably rely on multivariate modeling of markets and the economy. In this paper, we address three sources of error related to the modeling of these complex systems: 1. oversimplifying hypothesis; 2. uncertainties resulting from parameters' sampling error; 3. intrinsic non-stationarity of these systems.
arxiv
The Effect of Jasmine Aromatherapy on Short-Term Memory Performance
Guidena, 2022 This study aims to see how successful aromatherapy is at improving short-term memory in students at the State Islamic University of Sunan Ampel Surabaya.
Ramon Ananda Paryontri +1 more
doaj +1 more source
Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Paths [PDF]
Conference on Empirical Methods in Natural Language Processing, 2015 Relation classification is an important research arena in the field of natural language processing (NLP). In this paper, we present SDP-LSTM, a novel neural network to classify the relation of two entities in a sentence. Our neural architecture leverages
Yan Xu +5 more
semanticscholar +1 more source
Prediksi Pendapatan Kargo Menggunakan Arsitektur Long Short Term Memory
Jurnal Komputer Terapan, 2020 Angkutan kargo udara Indonesia saat ini mengalami perkembangan yang cukup signifikan. Salah satu layanan kargo yang terdapat di Indonesia yaitu Garuda Indonesia Cargo dan memiliki beberapa kantor cabang.
Bagas Aji Aprian +2 more
doaj +1 more source
Prioritizing Targets and Minimizing Distraction Within Limited Capacity Working Memory
Journal of Cognition, 2019 Oberauer (2019) maps out different perspectives that have emerged in exploring working memory and attention, and suggests particular ways in which these key aspects of cognition might operate in the service of successful goal completion.
Richard J. Allen
doaj +1 more source
Sensors, 2022 Short-term load forecasting is viewed as one promising technology for demand prediction under the most critical inputs for the promising arrangement of power plant units.
Lichao Sun +4 more
doaj +1 more source
Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks [PDF]
Proceedings of the Royal Society A, 2018 We introduce a data-driven forecasting method for high-dimensional chaotic systems using long short-term memory (LSTM) recurrent neural networks. The proposed LSTM neural networks perform inference of high-dimensional dynamical systems in their reduced ...
Pantelis R. Vlachas +4 more
semanticscholar +1 more source
Frontiers in Human Neuroscience, 2015 Performance on working memory (WM) tasks may partially be supported by long-term memory (LTM) processing. Hence, brain activation recently being implicated in WM may actually have been driven by (incidental) LTM formation. We examined which brain regions
Heiko eBergmann +6 more
doaj +1 more source
Rainfall–runoff modelling using Long Short-Term Memory (LSTM) networks
Hydrology and Earth System Sciences, 2018 . Rainfall–runoff modelling is one of the key challenges in the field of hydrology. Various approaches exist, ranging from physically based over conceptual to fully data-driven models.
Frederik Kratzert +4 more
semanticscholar +1 more source
Deep Sentence Embedding Using Long Short-Term Memory Networks: Analysis and Application to Information Retrieval [PDF]
IEEE/ACM Transactions on Audio Speech and Language Processing, 2015 This paper develops a model that addresses sentence embedding, a hot topic in current natural language processing research, using recurrent neural networks (RNN) with Long Short-Term Memory (LSTM) cells.
Hamid Palangi +7 more
semanticscholar +1 more source