Hiroshi Nakamine

Application of system theory to modeling of fish behavior

The construction of a mathematical model of fish behavior in the case where a fish school consists of many individuals is considered. The basic assumption for model building is that the schooling behavior of fish can be decomposed into two components: the motion of a representative of the school and the variation of the school form. The motion of the representative is expressed by a physical model, in which the main causes for the motion are described as the external forces. The variation of the school form is expressed by an autoregressive model. The parameters included in the model are estimated by using time-series data sampled from video image data recorded in a water tank experiment. The validity of the model is examined on the basis of computer simulation.<<ETX>>

A simulation study on adaptability to environmental variations based on ecological systems

Many ecological systems have an ability to adapt themselves to environmental variations and the adaptability varies with the structures of systems. In the paper, as an example of ecological systems, two kinds of fish school models with different characteristics are presented for investigating the adaptability to environmental variations. The model parameters are estimated by using the observation data obtained from water tank experiments. Various simulations are carried out for the case where an obstacle is set in the behavior space. The adaptability to environmental variations is examined by using the simulation results.

A Neural Network Model for Predicting the Error Rates of Students for a Learning Problem

In general it is impossible to know the learning effect of students before teaching them. Therefore, teachers have to predict it in order to perform actual teaching effectively and efficiently. In this paper, we propose a method to predict the error rates of the students for a learning problem and analyze how to teach students effectively through the prediction results. For this purpose, a multi-layer neural network (MNN) model is used. In this model, the input variables are five aptitude abilities of a student and the output variables are three error rates. It is confirmed that the prediction values obtained by using this MNN are reasonable as compared with the experimental results. Moreover, from the sensitivity analysis, the aptitude abilities to reduce the error rates are identified. This result makes it possible to predict the error rates of a learning problem in advance. By using these results, teachers can instruct students more effectively and efficiently.

An Ellipse Model for Describing the Form of Fish School

Abstract This paper deals with a mathametical model of the form of fish school moving in a water tank. The observation data is obtained by carrying out a water tank experinlent. The form of fish school is assumed to be an ellipse. The variables of the ellipse Inodel are major axis, minor axis and inclination. An autoregressive model is proposed to estinlate the time variation of the ellipse. The validity of the model is exalnined by a residual whiteness test and a prediction result. Further, the influence of the model paralneters on fish behavior patterns is investigated from the prediction result

A Mathematical Model for Growth of Sargassum Horneri and Its Environment

Seaweed plays an important role in aquatic ecosystem. It supplies nutrient and provides the place of life for many kinds of living organism in the sea. In order to control the marine resources reasonably, a study on the growth dynamics of seaweed is necessary. First, effects of solar radiation and water temperature on photosynthetic activity are considered. Secondly, a seasonal effect is introduced as a physiological phenomenon. Finally, a mathematical model of growth dynamics of Sargassum horneri is constructed from the idea of operating these effects multiplicatively. The model, parameters are determined on the basis of the observation data which were measured for Sargassum horneri at Notojima Aquarium, Ishikawa Prefecture. By a computer simulation, the weight of Sargassum horneri is estimated for any change of the environmental conditions.