Abstract: A method and a system for causing a neural circuit model to learn typical past control results of a process and using the neural circuit model for supporting an operation of the process. The neural circuit model is caused to learn by using, as input signals, a typical pattern of values of input variables at different points in time and, as a teacher signal, its corresponding values of the control variable. An unlearned pattern of input variables is inputted to the thus-learned neuron circuit model, whereby a corresponding value of the control variable is determined. Preferably, plural patterns at given time intervals can be simultaneously used as patterns to be learned.

Abstract: A method for causing a neural circuit model to learn typical past control results of a process and using the neural circuit model for supporting an operation of the process. The neural circuit model is caused to learn by using, as input signals, a typical pattern of values of input variables at different points in time and, as a teacher signal, its corresponding values of the control variable. An unlearned pattern of input variables is inputted to the thus-learned neuron circuit model, whereby a corresponding value of the control variable is determined. Preferably, plural patterns at given time intervals can be simultaneously used as patterns to be learned.

Abstract: A method and a system for causing a neural circuit model to learn typical past control results of a process and using the neural circuit model for supporting an operation of the process. The neural circuit model is caused to learn by using, as input signals, a typical pattern of values of input variables at different points in time and, as a teacher signal, its corresponding values of the control variable. An unlearned pattern of input variables is inputted to the thus-learned neuron circuit model, whereby a corresponding value of the control variable is determined. Preferably, plural patterns at given time intervals can be simultaneously used as patterns to be learned.

Abstract: In order to investigate an object, such as a culture of micro-organisms, the object is repeatedly captured at two different magnifications by a suitable image pick-up device. The images at the two different magnifications are then analysed by a suitable picture image recognition device and the results of the repeated analysis are compared, thereby to derive a measurement of the change in the object with time. Thus, for a culture of micro-organisms, the number of cells can be determined at one magnification and the number of microscopic spherical bodies can be determined at another magnification, to obtain a measure of the activity of the culture. Preferably, one or more conditions of the object are then controlled on the basis of the measurement of change.

Abstract: An apparatus for culturing animal cells, includes a diagnosis system to make it possible to diagnose by measuring sizes of the cells by means of image processing while a system of culturing the animal cells is cut off from the outside of the apparatus system, a control system to control the culture conditions of a culturing cistern on the basis of a result of the diagnosis, and a culture medium regenerating system to remove waste contents in a culture medium. In the apparatus of this invention, the culture system and diagnosis system are cut off from the outside of the apparatus system. Therefore, no infection of miscellaneous microorganism, etc., occurs, nor does consumption of valuable cells and products occur. Further, since it is possible to easily obtain data of the proportions of division potential-possessing cells and living cells, the environmental factors to the culturing cistern can be easily and instantly controlled based on the data, and therefore, the culturing efficiency can be enhanced.