Computational example sentences

"Computational" Example Sentences

1. Advancements in computational power are enabling new artificial intelligence applications.
2. Computational linguistics uses formal models and statistical methods to study and model human language.
3. With enough computational power, many problems that seem intractably difficult can be solved.
4. Molecular simulations using high-performance computational chemistry applications can model chemical systems at the atomic and molecular level.
5. Quantum computational techniques promise to revolutionize the fields of cryptography and optimization.
6. Computational fluid dynamics uses numerical analysis and data structures to model fluid flows.
7. Computational biology uses biological data and algorithms to model biological systems.
8. Computational neuroscience models neural processes using computational methods and mathematical models.
9. Computational nanotechnology designs and simulates nanoscale structures with computational models.
10. Computational archaeology uses computational tools and methods to model and interpret archaeological data.
11. Computationally intensive algorithms require high-performance computing resources to run efficiently.
12. The increasing computational power of graphics processing units is enabling new types of parallel computing applications.
13. The field of computational chemistry aims to solve chemical problems using computer simulations and modeling.
14. Computational financial modeling uses mathematical models to simulate financial processes and assets.
15. Computational physics employs mathematical models to describe complex physical systems via simulations.
16. Computational cognition studies human cognition through the development of cognitive models and simulations.
17. Computational complexity theory analyzes the computational complexity of problems and algorithms.
18. Big data analytics require massive computational resources to process and analyze very large data sets.
19. The massive computational demands of deep learning require specialized hardware like GPUs.
20. Computational geometry uses algorithms and data structures to model geometric objects.
21. Computational intelligence incorporates several computational techniques like neural networks, fuzzy systems and evolutionary computation.
22. Computational photography uses computational models and algorithms to enhance digital photographs.
23. Computational protein folding aims to predict the 3D shapes of proteins from their amino acid sequences.
24. Computational imaging employs computational techniques to capture and process images.
25. Computational evolutionary biology simulates the process of evolution using computational methods.
26. Graph algorithms are a class of computational techniques that operate on graph data structures.
27. Computational musicology analyzes musical data using computational models and algorithms.
28. Computational social science applies computational models and methods to social phenomena and human behavior.
29. Computational approaches can efficiently generate and analyze large numbers of candidates in drug discovery and materials design.
30. Computational optimization employs algorithms and modeling techniques to find optimal solutions to optimization problems.
31. Computational geometry algorithms can efficiently solve problems involving points, lines and polygons.
32. The field of computational complexity aims to understand the inherent complexity of computational problems.
33. Computational genomic approaches aim to understand complex biological systems at a genomic scale.
34. Computational physics applies numerical analysis and quantitative methods to solve physical problems.
35. Computational toxicology uses computer simulation and modeling to study the adverse effects of chemicals.
36. Computational statistics employs computational methods to analyze data and draw statistical inferences.
37. Computational nanoscience studies nanoscale phenomena through computer simulations and modeling.
38. Computational journalism uses algorithms, data and computational techniques in news reporting.
39. Computational design automates design processes through the use of computational models and tools.
40. Computational materials science employs simulations at the atomic scale to design novel materials.
41. Computational geometry employs algorithms and data structures for solving geometric problems.
42. Computational evolutionary genetics uses simulations to model how genetic mutations impact evolution.
43. Computational photography employs computational techniques to improve digital photographs.
44. Computational thinking involves breaking down problems into computational steps and algorithms.
45. Computational infrared astronomy analyzes infrared astronomical data with computational techniques.
46. Computational ecology uses modeling and simulations to study ecological systems.
47. Computational lexicography uses computers to analyze large linguistic corpora.
48. Computational sociology employs computer simulations and computational models to study social phenomena.
49. Computational astrophysics models complex astrophysical systems and phenomena via computer simulations.
50. Computational catalysis employs models and simulations at the molecular scale to design new catalysts.
51. Computational programs are software designed to perform computational operations and algorithms.
52. Computational simulations allow scientists to model complex systems that would be too difficult or expensive to study experimentally.
53. Computational methods, algorithms and models play an increasingly important role across science and engineering.
54. Computational approaches are essential for studying complex systems and problems that cannot be modeled analytically.
55. Computational skills involve proficiency in applying computational tools, algorithms and models to solve problems.
56. Computational thinking aims at developing cognitive and intellectual skills to solve problems using algorithms and models.
57. Computational tools and resources are essential for accelerating research progress in many scientific disciplines.
58. Exascale computational power represents the next frontier that will enable many new scientific discoveries.
59. Computational approaches can provide insights into systems that cannot be modeled or observed experimentally.
60. Computational research provides a powerful complement to theoretical and experimental work.

Common Phases

Computational power
Computational modeling
Computational problem
Computational resource
Computational approach
Computational method
Computational simulation
Computational demand
Computational speed
Computational complexity