Identifying Archetypes of an Enhanced System Dynamics Causal Loop Diagram in Pursuit of Strategies to Improve Smallholder Beef Farming in Java, Indonesia

Setianto, Novie Andri; Cameron, Donald; Gaughan, J. B.

doi:10.1002/sres.2312

Cited by 37 publications

(17 citation statements)

References 18 publications

(28 reference statements)

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“…Many problems are widespread in the fault diagnosis of modern control systems. Experts and scholars have proposed a variety of methods, such as: probability-based methods by Belief network [3], Markov Network [4], Dynamic causality diagram [5], fuzzy logic [6], neural network [7], evidence theory of dempster-Shafer [8], and so on. The dynamic causal map and fuzzy reasoning fusion method is to take the same object, use multiple sensors to comprehensively obtain various types of fault information, and finally make fault diagnosis.…”

Section: Introductionmentioning

confidence: 99%

Research on Fault Diagnosis Based on Dynamic causality diagram and Fuzzy Reasoning Fusion Method

2020

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With the progress of urbanization, the demand for elevators has upgraded from safe operation to comfortable, efficient, and all-round demand. The abnormal operation of the elevator is difficult to diagnose due to the complexity of the fault. This paper proposes a fault diagnosis method based on dynamic causality diagram and fuzzy reasoning. The dynamic causality diagram is extended, the intermediate module nodes are added, the description of the intermediate process of the elevator control system is solved, and the complete expression of knowledge is realized. The control timing of the elevator operation is introduced into the network structure of the dynamic causality diagram, which enhances the dynamic characteristics of the network. The causal cycle logic of the dynamic causality diagram is used to represent input and output signals and faults in elevator control systems. In the update of fuzzy rules, the real-time of fuzzy reasoning is enhanced, the search space of fuzzy rule matching is reduced, and the efficiency is improved. This paper combines actual field measurements and experimental data for fault diagnosis. Finally, the simulation, diagnosis and maintenance decision of the fault are realized, and an intelligent solution for elevator fault diagnosis is further proposed.

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Section: Introductionmentioning

confidence: 99%

Research on Fault Diagnosis Based on Dynamic causality diagram and Fuzzy Reasoning Fusion Method

2020

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“…Increased production and productivity are very important to be done by smallholder (Herrero et al, 2014). This is related to the amount of income earned for farmer household from the enterprise of beef cattle that is run (Setianto et al, 2014a). For household farmers, beef cattle are a main income for family survival, when household farmer are faced with difficult conditions, livestock can be sold to meet the needs (Setianto et al, 2014a).…”

Section: Introductionmentioning

confidence: 99%

Pattern of Integrated System of Smallholder Beef Cattle Central in Tegal Regency

et al. 2019

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Purpose of this research is to focus on importance of knowing the activities of smallholder enterprise systems, types and trends in the patterns of integrated systems adopted, the impact of implementing integrated systems and the implications for sustainability of livestock systems. This research also emphasize the importance of opportunities in enhancing and increasing livestock productivity and increasing production in smallholder farms and developing the easiest formulation of strategies for sustainable livestock systems. A qualitative method using Soft System Methodology (SSM) from System Thinking was chosen to visualize the activities of smallholder enterprise systems and the pattern of integrated systems are presented descriptively. The next study method of quantitative is used to determine the impact of livestock productivity on each applied integrated systems presented comparatively. Soft System Methodology succeed to visualize smallholder enterprise systems at the level of individual and community level of farmer. Farmer’s group activity influence the pattern of integrated systems that impacted on beef cattle’s productivity. The ICLFS pattern promotes a way of optimally utilizing agroecosystems and it has potential and become candidate system that be able in enhancing and increasing productivity, increasing livestock production and farmer's income, and realize beef self-sufficiency.

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“…Thus, developing beef farming will not only improve the national beef supply but also increase farmer's welfare. One recommended strategy for beef development in Indonesia is strengthening the breeding (Setianto et al, 2014a(Setianto et al, , 2014b.…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, side-tracking emphasizes that the reasons for recipients to adopt the development program are usually different from those motivating program designer (Olivier de Sardan, 2005). A study by Setianto et al (2014a) showed that government breeding program which initially designed for increasing the breeding cows were not fully adopted by farmers. Further, Setianto (2016) reported a Causal Loop Diagram which showed how government grant linked with cattle population, farming preference, and income.…”

Section: Introductionmentioning

confidence: 99%

Modeling How the Leader Power Affecting Performances of the Smallholder Beef Farming

2018

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This study aimed to explore how the leader power is affecting the performance of beef farmer group. The research was undertaken in two farmers group in Kabupaten Banjarnegara, Central Java Province involving 35 farmers and two beef traders. Systems thinking the approach was chosen about its capability to capture the complexity of the beef farming systems. A combination of semi-structured interviews, in-depth interviews, and workshop have been conducted to finalize this study. The discussion were focused on three aspects; (1) daily activities; (2) resources used and affected by those activities; and (3) pressures that are directly affected the resources and activities. The result was presented in a Causal Loop Diagram (CLD) which generated using Vensim® software. The CLD showed that leader power affects the group performance in two reinforcing loops. Firstly, leader power positively linked to the decision for allocating profit to group reinvestment. Secondly, for allocating proportion for breeding. Farmer's actual income become the leverage of the power dimension. Income will enforce the power thus makes the loop virtuous, whereas a loss will reduce power and makes the power loop vicious.

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Identifying Archetypes of an Enhanced System Dynamics Causal Loop Diagram in Pursuit of Strategies to Improve Smallholder Beef Farming in Java, Indonesia

Cited by 37 publications

References 18 publications

Research on Fault Diagnosis Based on Dynamic causality diagram and Fuzzy Reasoning Fusion Method

Research on Fault Diagnosis Based on Dynamic causality diagram and Fuzzy Reasoning Fusion Method

Pattern of Integrated System of Smallholder Beef Cattle Central in Tegal Regency

Modeling How the Leader Power Affecting Performances of the Smallholder Beef Farming

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