Real-valued strings

When these new binary strings are translated back into real values so that we can check what has happened, the result is... 

Molecular similarity and diversity methods typically represent molecules by a vector of real-valued properties (molecular weight, logP etc.) or binary values (0 for absence, 1 for presence of a substructure feature for example) in a bit-string or... 

Most of the formal analysis of the GA was based on the use of a discrete description of the chromosome. The binary alphabet (0 or 1) described so far is the one most commonly used, but other finite alphabets (e.g., the nucleic acid four-letter code, ACGT) have been analyzed and are known to exhibit the same behavior as the binary case. From a practical standpoint, it makes sense to dispense with the finite representation altogether and simply carry around realvalued strings as the chromosomes. Selection and crossover are identical, but mutation needs to be handled differently. Typically, the real-valued mutation operator selects a parameter to be mutated as before, but then adds a random increment to the value. The increment is drawn from a Gaussian distribution centered on the old value and having a user-specified width, thus adding one extra parameter to the method. 

Target values can be real values or have a binary (yes/no) form (see Bit String (or Bit Vector)). In such cases the weight maps of the output layer will show the probability distributions for the entire layout of neurons for being excited by an object with a particular property, or vice versa, if an unknown object excites a given neuron the answer retrieved from the output layer is the probability that the unknown object has that specific property. 

Both the modal daily consumption per occupant and the dependency on the household size are in accordance with data from other studies. This indieates that, in general, the composite proportional sampling deviee was operated correetly in the field test. There is some doubt over the apparently high eonsumption in one-person properties. These high values might stem from real high water use (e.g. tea, visitors, elderly people string at home all d ), but also from improper use of the deviee. Nevertheless no data have been excluded from the assessment on the basis of this eriterion. 

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