This paper aims to demonstrate how knowledge acquired from occupants' manual window operations can be implemented into BMS automated operation algorithms. Ten single-occupant offices were selected in a university building the UK. More than 28,000 hourly data points on indoor and outdoor temperature open area (OWA) analysed 2015 2020. The had adopted nine different algorithms during 5 years. cou...

Ordered Weighted Averaging (OWA) operators have been integrated in Convolutional Neural Networks (CNNs) for image classification through the OWA layer. This layer lets CNN integrate global information about early stages, where most architectures only allow exploitation of local information. As a side effect this integration, becomes practical method determination operator weights, which is usua...

Fuzzy rough set theory can be used as a tool for dealing with inconsistent data when there is gradual notion of indiscernibility between objects. It does this by providing lower and upper approximations concepts. In classical fuzzy sets, the are determined using minimum maximum operators, respectively. This undesirable machine learning applications, since it makes these sensitive to outlying sa...

Different types of aggregation operators such as the ordered weighted quasi-arithmetic mean (Quasi-OWA) operator and the normalized Hamming distance are studied. We introduce the use of the OWA operator in generalized distances such as the quasiarithmetic distance. We will call these new distance aggregation the ordered weighted quasi-arithmetic distance (Quasi-OWAD) operator. We develop a gene...

The OWA weighting vector and the fuzzy quantifiers are strictly related. An intuitive way for shaping a monotonic quantifier, is by means of the threshold that makes a separation between the regions of what is satisfactory and what is not. Therefore, the characteristics of a threshold can be directly related to the OWA weighting vector and to its metrics: the attitudinal character and the entro...

This paper addresses the blog distillation problem, that is, given a user query find the blogs that are most related to the query topic. We model each post as evidence of the relevance of a blog to the query, and use aggregation methods like Ordered Weighted Averaging (OWA) operators to combine the evidence. We show that using only highly relevant evidence (posts) for each blog can result in an...