Masahiro Tokumitsu

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An adaptive sensor network for home intrusion detection is proposed. The sensor network combines profile-based anomaly detection and adaptive information processing based on hidden Markov models (HMM) that allow the system to train and tune the profiles automatically. The trade-off between miss-alarms and false alarms has been studied experimentally.(More)
This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV). The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic(More)
In this study, a neural network technique is adopted to predict the electron flux in a geosynchronous orbit using several items of solar wind data obtained by ACE spacecraft and magnetic variations observed on the ground as input parameters. Parameter tuning for the back-propagation learning method is attempted for the feed-forward neural network. As a(More)
Space weather can be predicted using data from satellites. For example, the condition of high-energy electrons at geostationary orbit is vital in providing warnings for spacecraft operations. We investigate an adaptive predictor based on intelligent information processing. The predictor forecasts the condition of high-energy electrons at geostationary orbit(More)
This paper attempts to construct a resilient sensor network model with an example of space weather forecasting. The proposed model is based on a dynamic relational network. Space weather forecasting is vital for a satellite operation because an operational team needs to make a decision for providing its satellite service. The proposed model is resilient to(More)
We propose the concept of an adaptive strategy, and we consider its robustness against other strategies. On average, the adaptive strategy achieves a higher payoff than other strategies. The strength of a strategy is defined as an adaptive measure calculated on the basis of a payoff obtained through interactions among agents. An agent interacts with other(More)