Coal-fired boiler NOx emission prediction method based on intelligent KNN mechanism
A technology of coal-fired boilers and forecasting methods, applied in forecasting, computer components, data processing applications, etc., can solve the problems of expensive online monitoring instruments, increase the burden on power plants, and high operation and maintenance costs, and achieve easy promotion and use, Effects with low implementation difficulty and high compatibility
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[0030] The present invention will NO x The predictive model is converted to a KNN query processing extension model. Assume is the set of all real numbers, and ( d(·,·)) is an n-dimensional real vector space with a distance function d(·,·). suppose is a finite dataset / relation whose schema is R(tid,A 1 ,...,A n ), with n attributes (A 1 ,...,A n ) corresponds to where the i-th dimension Each t=(tid,t 1 ,...,t n ) ∈ R is associated with tid (tuple identifier). R is usually stored as a base table in a relational database system, and |R| represents the size of R, that is, the number of tuples in R.
[0031] Consider query points and an integer K, a KNN query (q,K) is to find in R the sorted set of K-tuples closest to q according to a given distance function d( , ). Assume K<|R|; otherwise, just retrieve all tuples in R. For simplicity, sometimes, KNN query (q, K) is denoted by q, and it is also called top-K, top-k, top-N query.
[0032] The distance function ...
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