scholarly journals Tree-Type Irrigation Pipe Network Planning and Design Method Using ICSO-ASV

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1985
Author(s):  
Zhen Li ◽  
Zijian Lin ◽  
Shilei Lyu ◽  
Zhiwei Wei ◽  
Heqing Huang
Keyword(s):  
Design Method ◽  
Network Planning ◽  
Control Group ◽  
Planning Model ◽  
Pipe Network ◽  
Swarm Optimization ◽  
Pipe Networks ◽  
Swarm Algorithm ◽  
Chicken Swarm Optimization ◽  
Tree Type

Research on tree-type irrigation pipe networks is an important component of agricultural water-saving projects. The optimal design of tree-type irrigation pipe networks is a key aspect regarding the profitability of irrigated agriculture. Meanwhile, swarm intelligence optimization algorithms have good computational ability and can be applied to solve many optimization problems in agricultural engineering. To identify the lowest investment cost for a pipe network, this study defined the concept of an upper water node to ensure the connectivity of tree-type irrigation pipe networks, and therefore, improve the pipe network planning model without using preliminary network connection diagrams. In addition, this study proposed an improved chicken swarm optimization algorithm (Improved Chicken Swarm Optimization using Adaptive Search and Variation, ICSO-ASV), which was applied to solve 12 test functions of different dimensions. The test results show that, compared to the traditional chicken swarm algorithm and other algorithms in the control group, the ICSO-ASV algorithm could effectively improve the global search capability. Finally, the ICSO-ASV algorithm was used to plan and design 15-node and 40-node pipe networks. The calculation results show that the average investment costs of the two pipe networks generated by the ICSO-ASV algorithm were 42.20% and 31.09% lower than those generated by the traditional chicken swarm algorithm, which further verified the feasibility of applying ICSO-ASV to design tree-type irrigation pipe networks. Thus, the design method proposed in this study can solve the optimal problems of tree-type irrigation pipe networks with varying topologies. The optimal solutions can be generated automatically using the ICSO-ASV algorithm if essential parameters of the pipe network planning model are provided.

scholarly journals Robust modeling and planning of radio-frequency identification network in logistics under uncertainties

2018 ◽  
Vol 14 (4) ◽  
pp. 155014771876978 ◽  
Author(s):  
Bowei Xu ◽  
Junjun Li ◽  
Yongsheng Yang ◽  
Octavian Postolache ◽  
Huafeng Wu
Keyword(s):  
Particle Swarm Optimization ◽  
Radio Frequency ◽  
Radio Frequency Identification ◽  
Cost Efficiency ◽  
Network Planning ◽  
Particle Swarm ◽  
Coverage Rate ◽  
Planning Model ◽  
Swarm Optimization ◽  
Frequency Identification

To realize higher coverage rate, lower reading interference, and cost efficiency of radio-frequency identification network in logistics under uncertainties, a novel robust radio-frequency identification network planning model is built and a robust particle swarm optimization is proposed. In radio-frequency identification network planning model, coverage is established by referring the probabilistic sensing model of sensor with uncertain sensing range; reading interference is calculated by concentric map–based Monte Carlo method; cost efficiency is described with the quantity of readers. In robust particle swarm optimization, a sampling method, the sampling size of which varies with iterations, is put forward to improve the robustness of robust particle swarm optimization within limited sampling size. In particular, the exploitation speed in the prophase of robust particle swarm optimization is quickened by smaller expected sampling size; the exploitation precision in the anaphase of robust particle swarm optimization is ensured by larger expected sampling size. Simulation results show that, compared with the other three methods, the planning solution obtained by this work is more conducive to enhance the coverage rate and reduce interference and cost.

Tree-Type Irrigation Pipe Network Planning Using an Improved Bat Algorithm

2019 ◽  
Vol 62 (2) ◽  
pp. 447-459 ◽  
Author(s):  
Shilei Lyu ◽  
Benlei Wu ◽  
Zhen Li ◽  
Tiansheng Hong ◽  
Jianhua Wang ◽  
...  
Keyword(s):  
Network Planning ◽  
Bat Algorithm ◽  
Planning Problem ◽  
Good Precision ◽  
Pipe Network ◽  
Local Optima ◽  
Improved Model ◽  
High Level ◽  
Tree Type ◽  
Self Adaptive

Abstract. A tree-type irrigation pipe network has a substantial role in saving water. To address the pipe network planning problem, an improved model is proposed by comprehensively considering the effects of various pipe network layouts and pipe diameters on the investment cost. The model can guarantee the water supply connectivity using the concept of high-level water nodes. Meanwhile, an improved self-adaptive bat algorithm with step-controlled and mutation mechanisms is proposed herein. The performance of the proposed algorithm is examined using 12 unimodal and multimodal functions. The experimental results reveal that the improved bat algorithm can effectively avoid local optima and exhibits high solution accuracy. Moreover, planning experiments are performed on the two pipe network cases. Results reveal that the proposed pipe network planning using the improved bat algorithm has a good precision and extendibility. Keywords: Bat algorithm, Pipe diameter optimization, Pipe network layout, Self-adaptive step, Tree-type pipe network.

scholarly journals Memetic chicken swarm algorithm for job shop scheduling problem

2019 ◽  
Vol 9 (3) ◽  
pp. 2075 ◽  
Author(s):  
Soukaina cherif bourki Semlali ◽  
Mohammed Essaid Riffi ◽  
Fayçal Chebihi
Keyword(s):  
Completion Time ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Swarm Optimization ◽  
Shop Scheduling ◽  
Swarm Algorithm ◽  
Chicken Swarm Optimization

<p>This paper presents a Memetic Chicken swarm optimization (MeCSO) to solve job shop scheduling problem (JSSP). The aim is to find a better solution which minimizes the maximum of the completion time also called Makespan. In this paper, we adapt the chicken swarm algorithm which take into consideration the hierarchical order of chicken swarm while seeking for food. Moreover, we integrate 2-opt method to improve the movement of the rooster. The new algorithm is applied on some instances of ORLibrary. The empirical results show the forcefulness of MeCSO comparing to other metaheuristics from literature in term of run time and quality of solution.</p>

scholarly journals A Joint Planning Method for Substations and Lines in Distribution Systems Based on the Parallel Bird Swarm Algorithm

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2669 ◽  
Author(s):  
Kuihua Wu ◽  
Kun Li ◽  
Rong Liang ◽  
Runze Ma ◽  
Yuxuan Zhao ◽  
...  
Keyword(s):  
Distribution Systems ◽  
Distribution Network ◽  
Network Planning ◽  
Mixed Integer ◽  
Planning Model ◽  
Joint Planning ◽  
Distribution Network Planning ◽  
Level Model ◽  
Swarm Algorithm ◽  
Bird Swarm Algorithm

Reasonable distribution network planning schemes can not only improve the power quality and power supply capacity of the power system, but also increase the economic benefits and welfare of the whole society. In this work, a bi-level optimization model is proposed for the joint planning of substations and lines in looped urban distribution systems. The upper-level model aims to address the substation locating and sizing problem, whereas the lower-level model the network planning problem. Both the substations directly supplying power to a load and the contralateral substations that act as backup power source to the load are considered in the bi-level model. In order to solve the bi-level planning model which is mathematically mixed integer programing and with plenty of continuous and discrete variables, the bird swarm algorithm is improved and applied based on the idea of parallel computing of big data theory. Simulations on actual planning problems are employed to verify the effectiveness of the proposed bi-level distribution network planning model and the parallel bird swarm algorithm.

Pengaruh Konsumsi Cookies Kerang Dara (Anadara Granosa) terhadap Perubahan Kadar Haemoglobin Wanita Usia Subur

2020 ◽  
Vol 7 (2) ◽  
pp. 169-179 ◽  
Author(s):  
Vera Iriani Abdullah ◽  
C.H Haumahu
Keyword(s):  
Data Collection ◽  
Perinatal Death ◽  
Design Method ◽  
Statistical Tests ◽  
Total Sample ◽  
Control Group ◽  
Childbearing Age ◽  
Control Group Design ◽  
Quasi Experimental ◽  
Anadara Granosa

In the world, around 1.62 billion people have low HB levels, around 30.2% occur in the group of women aged 15-49. In Indonesia, anemia cases rank 4th in the top 10 most disease groups. Prolonged iron deficiency can cause anemia, so it needs to be treated immediately so it doesn’t continue into pregnancy age which can cause complications until maternal and perinatal death. Papua has an abundance of marine wealth; one of those is Kerang Dara. Through this study, researchers wanted to explore the health benefits of nature. The aim is to see the effect of Consumption of Kerang Dara Cookies (Anadara Granosa) on Changes of Hemoglobin Levels of in Woman of Childbearing Age as an Effort to Prevent Anemia in District Aimas, Klaigit Village. Type of this research is quasi-experimental by pretest-posttest control group design method. The population of all the women of Childbearing who live in Klaigit Village, with a total sample of 14 people divided into 2 groups: control and intervention. Data collection techniques using random sampling. The time of data collection occurred for 2 weeks, starting from September 20th to October 4th. The results based on statistical tests using T-Test, then the value 884 is greater than the value of the table 0.05, then the conclusion is there is an Effect of Consumption Kerang Dara Cookies (Anadara Granosa) Towards the Increased of Woman of Childbearing Hemoglobin Levels in Klaigit Village in District Aimas in 2019.

PENGARUH MEDIA GAMBAR TERHADAP KEMAMPUAN MENULIS PUISI SISWA

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Sinta Maria Dewi
Keyword(s):  
Design Method ◽  
Writing Skills ◽  
Class Action ◽  
T Test ◽  
Control Group ◽  
Control Group Design ◽  
Media Image ◽  
Group Design ◽  
Random Method ◽  
Paired T Test

Abstract: This research aims to know the Influence of Media Image on the ability of Writing Poetry students. The method used in this study is a random method that does not use posttes control group design method. The findings of this study show the average way of writing poetry on students by using the image media (experimental class) higher average poetry writing skills on students who were taught with conventional learning (control class). The average of pretest experiments obtained by experiment class is 63,75. The average pretest class of control class is 61,05. After the second class action, the average posttest of the experimental class is 79.45 and the control class is 74.95. Hypothesis calculation using t paired t test test and significance of 0.05 significant level indicates probability (significance) is 0,033. Because of the significance of 0.033

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