algorithm)
int gcd(int u, int v)
{
while (u > 0) {
if (u < v) SWAP(u, v);
u = u - v;
}
return v;
}
다음의 프로그램은 알고리즘인가?
[3N + 1 문제]
read N
while (N != 1) {
if (N is even)
N = N / 2;
else
N = 3*N + 1;
}
알고리즘적인 문제 (algorithmic problem)
해답의 정
(Tabu Search Algorithm) 및 개미군집 최적화(Ants Colony Optimization)를 이용하여 예방정비 비용을 최소화 시키는 정비 주기와 단위시간당 기대비용값을 산출하고 시간적 효율성을 판단함으로써 최적해에 빠르게 수렴하는 메타휴리스틱 알고리즘을 비교하여 다부품 시스템 최적화 결정에 효과적임을 고찰한다.
algorithms to optimize operations and improve overall performance.
4차 산업혁명의 핵심 특징 중 하나는 사물인터넷(IoT), 빅데이터, 인공지능(AI) 등의 기술을 융합해 지능화된 시스템을 만드는 것이다. 유비쿼터스 컴퓨팅은 이러한 기술이 서로 그리고 물리적 환경과 상호 작용할 수 있는 플랫폼을 제공함으로써 중요
and it cause the serious problem in parking lots. Some of the car owners spend their time to take their tasks in airport after parallel parking or illegal parking their cars, it could not be solved until they come back here and distance between parking lots and airport is quite far so that waiting time for car owner is also long. In the case that the owner stay abroad, the problem become worse.
parallel software running on tens, hundreds, or even thousands of servers".)
Big data which is schema-less and unstructured type of data already exists for several years. But lack of mgt capability on huge and unstructured data, it was thrown out or used as a sample. However as tech grows, there’s a possibility of analyze Big data.
Big data can be used to create added value on business.
과학기술 분야에서 큰규모의 문제를 해결하기 위해서 대규모 분산 컴퓨팅 기술이 이용되고 있다 [7].일반적인 분산 컴퓨터는 이기종의 컴퓨팅 노드로 이루어져 있기 때문에, 분산 컴퓨터의 자원을 효율적으로 사용하기 위해서는 성능이 우수한 스케줄링 알고리즘이 필요하다. 이기종 분산 컴퓨터를 위
1.Preferred study field in detail
My passion for engineering stems from a profound fascination with the intricacies of mechanics and the endless possibilities it offers for innovation and problem-solving. From the graceful efficiency of mechanical systems to the elegant design of cutting-edge machinery, I am captivated by the dynamic interplay of forces and materials that shape our modern wor
1. Trends in Analytical Techniques
The most popular word that describes today’s analytics is machine learning. In almost every analytical application that companies develop today involves in machine learning techniques. For example, decision trees predict which employee is likely to leave or which customer will stop using a cell phone service. In customer recommendation systems, KNN (K Nearest