This survey focuses on the problem of parameters selection in image edge detection by ant colony optimization (ACO) algorithm. By introducing particle swarm optimization (PSO) algorithm to optimize parameters in ACO algorithm, the fitness function based on connectivity of image edge is proposed to evaluate the quality of parameters in ACO algorithm. And the ACO-PSO algorithm is applied to image...

Background Emphysema is a distinct feature for classifying COPD, and smoking history (≥10 pack-years) is one of several newly proposed criteria for asthma-COPD overlap (ACO). We studied whether or not a smoking history (≥10 pack-years) and emphysema are useful markers for classifying ACO and differentiating it from asthma with chronic airflow obstruction (CAO). Methods We retrospectively stud...

Any Colony Optimization (ACO) [1] ACO มีลักษณะการหาอาหารของมด ซึ่งเป็นวิวัฒนาการของพฤติกรรมทางสังคม (Social Behavior) แทนที่จะเป็นทางด้านพันธุกรรม ACO ถูกคิดค ้ นโดย Dorigo และคณะ [1] ซึ่งเลียน แบบพฤติกรรมการหาอาหารของมดโดยค้นการหาเส้นทางที่สั้นที่สุดระหว่างรังกับแหล่งอาหาร โดยใช้ฟีโรโมน ) Pherom on ) ที่มดวางไว้ระหว่างทางเพื่อใช้ในการสื่อสารทางอ้อมกับมดตัวอ่ืน ใน ฝูง ในระหว่างการเดินทางหากเจอสิ่งกีดขวางมดแต่ละตัวจะตัดสิ...

Under the “Double Carbon” background, development of green agricultural machinery is very fast. An important factor that determines performance electric farm endurance capacity, which directly related to running path machinery. The optimized driving can reduce operating loss and extend mileage machinery, then multi-node planning helps improve working efficiency tractors. Ant Colony Optimization...

Ant Colony Optimization (ACO) is a well-known metaheuristic in which a colony of artificial ants cooperates in exploring good solutions to a combinatorial optimization problem. In this paper, an ACO algorithm is presented for the graph coloring problem. This ACO algorithm conforms to Max-Min Ant System structure and exploits a local search heuristic to improve its performance. Experimental resu...

Optimization of reservoir parameters is an important issue in petroleum exploration and production. The Ant Colony Optimization(ACO) is a recent approach to solve discrete and continuous optimization problems. In this paper, the Ant Colony Optimization is usedas an intelligent tool to estimate reservoir rock properties. The methodology is illustrated by using a case study on shear wave velocity...

Wavelength selection is one of the key steps in quantitative spectral analysis, which reduces computation time while also improving prediction accuracy model. In this paper, we propose a wavelength algorithm based on ant colony optimization (ACO), absolute value regression coefficient multiple linear (MLR) model used as basis for evaluating importance wavelengths, and after full MLR modeling in...

Software Regression Testing (SRT) helps with the modified code to ensure that no other new defects have been trained and significantly impact existing code. SRT is a time cost taking process. Test Case Prioritization (TCP) reschedule test cases (TC’S) picks according prioritization, which allows software testers maximize number of faults detected within given frame. Ant Colony Optimization (ACO...

In the paper we present recommendation of student courses using Ant Colony Optimization (ACO). ACO is proved to be effective in solving many optimization problems, here we show that ACO also in the problem of prediction of final grades students receives on completing university courses is able to deliver good solutions. To apply ACO in any recommender system we need special problem representati...