Journal of Intelligent & Fuzzy Systems - Volume 44, issue 4

Authors: Kabilesh, S.K. | Mohanapriya, D. | Suseendhar, P. | Indra, J. | Gunasekar, T. | Senthilvel, N.

Article Type: Research Article

Abstract: Monitoring fruit quality, volume, and development on the plantation are critical to ensuring that the fruits are harvested at the optimal time. Fruits are more susceptible to the disease while they are actively growing. It is possible to safeguard and enhance agricultural productivity by early detection of fruit diseases. A huge farm makes it tough to inspect each tree to learn about its fruit personally. There are several applications for image processing with the Internet of Things (IoT) in various fields. To safeguard the fruit trees from illness and weather conditions, it is difficult for the farmers and their workers …to regularly examine these large areas. With the advent of Precision Farming, a new way of thinking about agriculture has emerged, incorporating cutting-edge technological innovations. One of the modern farmers’ biggest challenges is detecting fruit diseases in their early stages. If infections aren’t identified in time, farmers might see a drop in income. Hence this paper is about an Artificial Intelligence Based Fruit Disease Identification System (AI-FDIS) with a drone system featuring a high-accuracy camera, substantial computing capability, and connectivity for precision farming. As a result, it is possible to monitor large agricultural areas precisely, identify diseased plants, and decide on the chemical to spray and the precise dosage to use. It is connected to a cloud server that receives images and generates information from these images, including crop production projections. The farm base can interface with the system with a user-friendly Human-Robot Interface (HRI). It is possible to handle a vast area of farmland daily using this method. The agricultural drone is used to reduce environmental impact and boost crop productivity. Show more

Keywords: Fruit quality, Internet of Things (IoT), fruit disease, artificial intelligence, drone system

DOI: 10.3233/JIFS-222017

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 4, pp. 6593-6608, 2023

Authors: Long, Le Ngoc Bao | Kim, Hwan-Seong | Cuong, Truong Ngoc | You, Sam-Sang

Article Type: Research Article

Abstract: Pricing and production policies play a key role in ensuring the added value of supply chain systems. For perishable inventory management, the pricing and production lines must be manipulated dynamically since several uncertainties are involved in the system’s behavior. This study discusses the impact of dynamic pricing and production policies on an uncertain stochastic inventory system with perishable products. The mathematical model of the inventory management system under external disturbance is formulated using a continuous differential equation in which the price and production rates are considered as control factors to optimize total profits, which is described as an objective …function. An analytical solution for the optimal pricing and production rate was obtained using the Hamilton-Jacobi-Bellman equation. The unknown disturbance was approximated using an intelligent approach called radial basis function neural network. Finally, extensive numerical simulations were presented to validate the theoretical results and optimization solutions (including the efficiency of the approximation of the unknown disturbance) for the dynamic pricing and production management strategy of an uncertain stochastic inventory system against volatile markets. The performance of the proposed method was analyzed under different stock level conditions, which highlighted the importance of keeping the inventory levels at an optimal range to ensure the profitability of business operations. This management strategy can assist a business with solutions for inventory policies while supporting decision-making processes to facilitate coping with production management disruptions. Show more

Keywords: Optimization, uncertain stochastic system, production-inventory system, perishable products, adaptive neural networks

DOI: 10.3233/JIFS-222804

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 4, pp. 6609-6629, 2023

Authors: Faiza, | Khalil, K.

Article Type: Research Article

Abstract: This study envisages assessing the effects of the COVID-19 on the on-time performance of US-airlines industry in the disrupted situations. The deep learning techniques used are neural network regression, decision forest regression, boosted decision tree regression and multi class logistic regression. The best technique is identified. In the perspective data analytics, it is suggested what the airlines should do for the on-time performance in the disrupted situation. The performances of all the methods are satisfactory. The coefficient of determination for the neural network regression is 0.86 and for decision forest regression is 0.85, respectively. The coefficient of determination for the …boosted decision tree is 0.870984. Thus boosted decision tree regression is better. Multi class logistic regression gives an overall accuracy and precision of 98.4%. Recalling/remembering performance is 99%. Thus multi class logistic regression is the best model for prediction of flight delays in the COVID-19. The confusion matrix for the multi class logistic regression shows that 87.2% flights actually not delayed are predicted not delayed. The flights actually not delayed but wrongly predicted delayed are12.7%. The strength of relation with departure delay, carrier delay, late aircraft delay, weather delay and NAS delay, are 94%, 53%, 35%, 21%, and 14%, respectively. There is a weak negative relation (almost unrelated) with the air time and arrival delay. Security delay and arrival delay are also almost unrelated with strength of 1% relationship. Based on these diagnostic analytics, it is recommended as perspective to take due care reducing departure delay, carrier delay, Late aircraft delay, weather delay and Nas delay, respectively, considerably with effect of 94%, 53%, 35%, 21%, and 14% in disrupted situations. The proposed models have MAE of 2% for Neural Network Regression, Decision Forest Regression, Boosted Decision Tree Regression, respectively, and, RMSE approximately, 11%, 12%, 11%, respectively. Show more

Keywords: Air transport, airline flight delays, artificial intelligence, machine learning

DOI: 10.3233/JIFS-222827

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 4, pp. 6631-6653, 2023

Authors: Stephen, M. | Felix, A.

Article Type: Research Article

Abstract: The World health organization (WHO) reported that cardiovascular disease is the leading cause of death worldwide, particularly in developing countries. But while diagnosing cardiovascular disease, medical practitioners might have differences of opinions and faced challenging when there is inadequate information and uncertainty of the problem. Therefore, to resolve ambiguity and vagueness in diagnosing disease, a perfect decision-making model is required to assist medical practitioners in detecting the disease at an early stage. Thus, this study designs a fuzzy analytic hierarchy process (FAHP) point-factored inference system to detect cardiovascular disease. The attributes are selected and classified into sub-attributes and point factor …scale using the clinical data, medical practitioners, and literature review. Fuzzy AHP is used in calculating the attribute weights, the strings are generated using the Mamdani fuzzy inference system, and the strength of each set of fuzzy rules is calculated by multiplying the attribute weights with the point factor scale. The string weights determine the output ranges of cardiovascular disease. Moreover, the results are validated using sensitivity analysis, and comparative analysis is performed with AHP techniques. The results show that the proposed method outperforms other methods, which are elucidated by the case study. Show more

Keywords: Linguistic variable, fuzzy rules, FAHP, point factor scale, inference system, cardiovascular disease

DOI: 10.3233/JIFS-223048

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 4, pp. 6655-6684, 2023

Authors: Jeba Emilyn, J. | Ashokkumar, M.

Article Type: Research Article

Abstract: In Wireless Sensor Networks (WSNs), Clustering aids in maximizing the lifetime of the network with sustained energy stability in the sensor nodes during data dissemination. In this clustering process, the sensor nodes are organized into clusters with the potential fitness node designated as Cluster Heads (CHs) for collecting and forwarding the data to the sink. In specific, the energy consumption of sensor nodes during their role as CH is maximized with great impact over the network lifespan. In this paper, a Weight-imposed Elite Hybrid Binary Cuckoo Search (EHBCS)-based Clustering Mechanism is proposed for facilitating potent data transmission with minimized energy …consumption and improved network lifetime. This EHBCS is proposed as a novel energy-sensitive CH selection framework based on the process of hierarchical routing through the inclusion of hybrid optimization algorithm. It selected CH depending on the parameters of Quality of Service (QoS), delay, distance, and energy into account. It integrated the merits of Binary Cuckoo Search and Elite Mechanism for selecting CHs and performing effective processes by preventing sinkhole issues in WSNs. The results of EHBCS confirmed better throughout by 11.32%, minimized energy consumption by 13.84%, and minimized delay by 16.12% with an increasing number of sensor nodes, compared to the baseline CH selection approaches used for exploration. Show more

Keywords: Binary cuckoo search, clustering, cluster head selection, elite solution, crossover, mutation

DOI: 10.3233/JIFS-222137

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 4, pp. 6685-6698, 2023

Authors: Liu, Hongqi | Liu, Yulei

Article Type: Research Article

Abstract: A new three-dimensional college performance assessment index system is established. The grey relational method is used to evaluate college performance in a university and the CRITIC method of variation coefficient is used to weight the assessment indices. The performance of 15 colleges in NH University are assessed by using the index system and the grey method, and the results can supply some important information for management optimization and resource distribution of NH University. It also shows that the index system and grey assessment model proposed in this paper have good potential to solve the similar problem.

Keywords: Performance assessment, university, Grey relational analysis

DOI: 10.3233/JIFS-223286

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 4, pp. 6699-6708, 2023

Authors: Fan, Ruguo | Chen, Fangze | Wang, Yitong | Wang, Yuanyuan | Chen, Rongkai

Article Type: Research Article

Abstract: In the practice of COVID-19 prevention and control in China, the home quarantine policy directly connects and manages the residents, which plays a significant role in preventing the spread of the epi-demic in the community. We evaluate the effectiveness of current home quarantine policy in the actual execution process based on the evolutionary game relationship between the community and res-idents. This paper establishes a double-layer coupled complex network game model, and uses the multi-agent modeling method to study the game relationship between the community and residents in the context of home quarantine policies. The results show that initial strategy of …the community with strict supervision and reasonable government reward allocation will increase the proportion of the residents complying with the quarantine rule. When 80% of the communities chose to supervise strictly at the beginning, people are more likely to follow the rules. While when the residents can only get 20% of the government’s reward, the proportion of choosing to violate the quarantine rules is much higher than that when they can get 80% of the reward. Besides, the structure of small-world network and environmental noise will also affect the residents’ strategy. As the probability of reconnection of the small-world network rises from 0.2 to 0.8, the proportion of residents who choose to comply with the strategy becomes much higher. When the environmental noise reaches 0.5, the ratio of residents who choose to violate the strategy is higher than the ratio of complianc. The study is helpful to provide the basis for the government to formulate the quarantine policy and propose an optimization for making effective quarantine measures. In this way, the government can adjust the parameters to make residents achieve the possible level of compliance with quarantine policies as high as possible to contain the spread of the epidemic. Show more

Keywords: COVID-19, evolutionary game, double-layer net-work, agent-based modelling, small-world network

DOI: 10.3233/JIFS-221594

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 4, pp. 6709-6722, 2023

Authors: Zhang, Zhichao | Cheng, Xinghui | Zhao, Weifeng | Zhang, Qing

Article Type: Research Article

Abstract: With the development of complexity in complex equipment, the selection of suppliers referred to several groups. How to select the suppliers for the complex equipment under several groups becomes an important topic. To solve the problem, a two-level consensus reaching process is designed to select the suppliers of the complex equipment in uncertain environments. First, considering the fuzzy environment of selection, the cloud model, which could reflect the fuzziness and randomness, is used to present the uncertain preferences of the decision-makers. Then, considering the negotiation and interaction of two groups, the bi-level consensus reaching process is established to present the …master-slave features of complex equipment. Third, to solve the proposed bi-level model, the improved artificial bee colony is proposed, which adopts the gray wolf algorithm’ searching mechanism and levy flying method. The adopted strategies could enhance the searching power of artificial bee colony. Finally, a case study is used to verify the advantages of our study. Show more

Keywords: Decision making, mathematical modelling, fuzzy logic, supply chain management

DOI: 10.3233/JIFS-221903

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 4, pp. 6723-6736, 2023

Authors: Gong, Zengtai | He, Lele

Article Type: Research Article

Abstract: Connectivity parameters play a crucial role in network analysis. The cyclic reachability is an important attribute that determines the connectivity of the network, the strength of the cycles in intuitionistic fuzzy graphs (IFGs) is not unique. This article first introduces several concepts of cycle connectivity of IFGs, and then discusses the related properties. On the basis of the cycle connectivity of IFGs, the concepts of cyclic connectivity index ( CCI ) and average cyclic connectivity index ( ACCI ) are proposed, which can be used to express the reachability of …cycle. Some results of CCI on IFGs are discussed, such as cutvertices, trees, and complete intuitionistic fuzzy graphs. The vertices of IFGs are divided into three categories according to ACCI . Two algorithms are introduced, one to find CCI and ACCI of a given IFGs and the other to identify the nature of vertices. Show more

Keywords: Cycle connectivity, intuitionistic fuzzy graphs, cyclic connectivity index

DOI: 10.3233/JIFS-222332

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 4, pp. 6737-6748, 2023

Authors: Swethaa, S. | Felix, A.

Article Type: Research Article

Abstract: Land, marine and airborne are the three types of military robots used in the war-field. Land robots are the most crucially considered robots. Selecting a military land robot for a specific purpose is one of the challenging problems for a decision-maker to find the most preferred alternative when it involves fuzziness and uncertainty. Intangible factors are used while selecting the appropriate robotic system as it effectively deals with fuzziness. Intuitionistic dense fuzzy set, which is the combination of intuitionistic fuzzy set and dense fuzzy set, is capable of dealing with intangible factors. This study aims to design the integrated model …on intuitionistic dense fuzzy AHP-TOPSIS to choose the most preferable military land robots under various circumstances. Robots for different types of situations, namely bomb disposal, search and rescue, surveillance and reconnaissance and war-fighter are considered. Moreover, the intuitionistic dense fuzzy AHP is utilized to calculate the subjective weights of the criteria and intuitionistic dense fuzzy TOPSIS is used to rank the alternatives. Further, a sensitivity analysis is examined to demonstrate the quality of the outcome and the results are compared with the fuzzy set, intuitionistic fuzzy set, and dense fuzzy set to show the efficiency of the proposed methodology. Show more

Keywords: Robot selection, intuitionistic dense fuzzy set, intuitionistic trapezoidal dense fuzzy AHP, intuitionistic trapezoidal dense fuzzy TOPSIS

DOI: 10.3233/JIFS-223622

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 4, pp. 6749-6774, 2023