1. A method for predicting one or more operating parameters of a technical system, wherein one or more input variables are supplied, via an input layer (I), to a neural network (NN), the method for predicting comprising a modeling method for the computer-assisted modeling of the technical system, the modeling method comprising: modeling one or more output vectors on the basis of one or more input vectors by a learning process of the neural network (NN) based on training data comprising known input vectors and output vectors, a respective output vector comprising one or more operating variables of the technical system and a respective input vector comprising one or more input variables which influence the operating variable(s); wherein the neural network (NN) is a feed-forward network comprising the input layer (I), a plurality of hidden layers (H 1 , H 2 , H 3 ) and an output layer (O), the input layer (I) containing a number of input neurons for describing the input vector(s), and each respective hidden layer (H 1 , H 2 , H 3 ) containing a number of hidden neurons, and the output layer (O) containing a number of output neurons for describing the output vector(s); and wherein the input layer, the plurality of hidden layers and the output layer are connected to one another and wherein the output layer (O) comprises a plurality of output clusters (O 1 , O 2 , O 3 ) each comprising one or more output neurons, and each output cluster being assigned and connected to one of the hidden layers only, and each output cluster (O 1 , O 2 , O 3 ) describing the same output vector as the other output clusters, wherein the technical system is a wind power installation or a photovoltaic installation; wherein a first input vector comprises, as input variables, one or more predicted environmental conditions for a future time from a plurality of future times, and wherein the predicted environmental condition(s) are weather data comprising at least one of the following variables: ambient temperatures; humidity values; wind speeds; wind directions: values relating to the cloud cover of the sky; and solar radiation values; wherein a first output vector comprises, as operating variables, amounts of energy (ES) generated by the energy generation installation for a plurality of successive future times, an amount of energy (ES) being the amount of energy generated between two successive future times; the neural network (NN) determines, using the first input vector, the first output vector having one or more operating parameters of the technical system for at least one output cluster (O 1 , O 2 , O 3 ) of the output layer (O); and adjusting an amount of energy sold on an energy market, wherein the amount of energy sold is generated by the wind power installation or the photovoltaic installation based on the first output vector; or supplying predicted generated energy based on the first output vector as control energy in an energy network.