Sentence examples for heuristic terms from inspiring English sources

This article extends previous works [11 13] where two feature extraction techniques (heuristic terms and aspects) were proposed and evaluated using a small dataset.

In this dataset, in turn, the classification terms approach performed statistically better than the heuristic terms approach, also considering a value of p<0.001.

In this work, we first propose four variants (termed as heuristics III through VI) of our earlier heuristic (termed as heuristic II) and compare all of them with other published heuristics in respect of execution time and solution cost.

The sixth paper of this issue: Investigating TSP Heuristics for Location-Based Services by Weihuang Huang and Jeffrey Xu Yu, investigates 22 heuristics and shows the best heuristics in terms of accuracy and efficiency using benchmarks, real datasets, and synthetic datasets.

Our experimentation shows that general variable neighborhood search based heuristics outperform the best-known heuristics in terms of solution quality and computational effort.

In this work, we investigate 22 heuristics and show that the best heuristics in terms of accuracy for LBS are not the ones suggested by the existing work, and identify several heuristics by extensive performance studies over real datasets, TSPLIB benchmarks, the existing synthetic datasets and our new synthetic datasets.

In order to better understand the heuristics in real applications for LBS, we study the 22 heuristics in terms of accuracy using the new synthetic datasets proposed in this work.

In an extensive computational study, we assess the performance of these heuristics in terms of quality and efficiency.

Though a few reviews have been presented, some latest methods are not included and there is no comparison of the meta-heuristics in terms of their performances.

The paper argues that the construction of a heuristic we term the fisheries problematic, around issues and contexts, reveals the breadth of international fisheries management concerns and the variety of contexts in which these concerns are being faced.

Notably, we compare online and offline heuristics in terms of energy savings and LSP acceptance rates.