Lifan Zhao^1,2, Zetian Huang^1,2, Qiming Fu^1,2,3,*, Nengwei Fang⁴, Bin Xing⁴, Jianping Chen^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2741-2758, 2023, DOI:10.32604/cmes.2023.025500 - 09 March 2023

Abstract Aiming at optimizing the energy consumption of HVAC, an energy conservation optimization method was proposed for HVAC systems based on the sensitivity analysis (SA), named the sensitivity analysis combination method (SAC). Based on the SA, neural network and the related settings about energy conservation of HVAC systems, such as cooling water temperature, chilled water temperature and supply air temperature, were optimized. Moreover, based on the data of the existing HVAC system, various optimal control methods of HVAC systems were tested and evaluated by a simulated HVAC system in TRNSYS. The results show that the proposed More >

Zhengkai Ding^1,2, Qiming Fu^1,2,*, Jianping Chen^2,3,4,*, You Lu^1,2, Hongjie Wu¹, Nengwei Fang⁴, Bin Xing⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2759-2785, 2023, DOI:10.32604/cmes.2023.026091 - 09 March 2023

Abstract The optimization of multi-zone residential heating, ventilation, and air conditioning (HVAC) control is not an easy task due to its complex dynamic thermal model and the uncertainty of occupant-driven cooling loads. Deep reinforcement learning (DRL) methods have recently been proposed to address the HVAC control problem. However, the application of single-agent DRL for multi-zone residential HVAC control may lead to non-convergence or slow convergence. In this paper, we propose MAQMC (Multi-Agent deep Q-network for multi-zone residential HVAC Control) to address this challenge with the goal of minimizing energy consumption while maintaining occupants’ thermal comfort. MAQMC… More >

Vineet Sharma¹, Mohammad Zubair Khan^2,*, Shivani Batra¹, Abdullah Alsaeedi³, Prakash Srivastava⁴

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1211-1231, 2023, DOI:10.32604/csse.2023.029184 - 03 November 2022

Abstract The amount of needed control messages in wireless sensor networks (WSN) is affected by the storage strategy of detected events. Because broadcasting superfluous control messages consumes excess energy, the network lifespan can be extended if the quantity of control messages is decreased. In this study, an optimized storage technique having low control overhead for tracking the objects in WSN is introduced. The basic concept is to retain observed events in internal memory and preserve the relationship between sensed information and sensor nodes using a novel inexpensive data structure entitled Ordered Binary Linked List (OBLL). Whenever More >

Nandhi Kesavan^*, Latha

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 327-337, 2023, DOI:10.32604/iasc.2023.030910 - 29 September 2022

Abstract Climate change is the most serious causes and has a direct impact on biodiversity. According to the world’s biodiversity conservation organization, reptile species are most affected since their biological and ecological qualities are directly linked to climate. Due to a lack of time frame in existing works, conservation adoption affects the performance of existing works. The proposed research presents a knowledge-driven Decision Support System (DSS) including the assisted translocation to adapt to future climate change to conserving from its extinction. The Dynamic approach is used to develop a knowledge-driven DSS using machine learning by applying More >

Talal H. Noor^1,*, El-Sayed Atlam², Abdulqader M. Almars¹, Ayman Noor³, Amer S. Malki¹

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3785-3799, 2023, DOI:10.32604/iasc.2023.032250 - 17 August 2022

Abstract With the increase of energy consumption worldwide in several domains such as industry, education, and transportation, several technologies played an influential role in energy conservation such as the Internet of Things (IoT). In this article, we describe the design and implementation of an IoT-based energy conservation smart classroom system that contributes to energy conservation in the education domain. The proposed system not only allows the user to access and control IoT devices (e.g., lights, projectors, and air conditions) in real-time, it also has the capability to aggregate the estimated energy consumption of an IoT device,… More >

Thongchai Botmart¹, Zulqurnain Sabir^2,3, Afaf S. Alwabli⁴, Salem Ben Said², Qasem Al-Mdallal², Maria Emilia Camargo⁵, Wajaree Weera^1,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5589-5607, 2022, DOI:10.32604/cmc.2022.032087 - 28 July 2022

Abstract The motive of this work is to present a computational design using the stochastic scaled conjugate gradient (SCG) neural networks (NNs) called as SCGNNs for the socio-ecological dynamics (SED) with reef ecosystems and conservation estimation. The mathematical descriptions of the SED model are provided that is dependent upon five categories, macroalgae M(v), breathing coral C(v), algal turf T(v), the density of parrotfish P(v) and the opinion of human opinion X(v). The stochastic SCGNNs process is applied to formulate the SED model based on the sample statistics, testing, accreditation and training. Three different variations of the SED have been… More >

Hongly Va¹, Min-Hyung Choi², Min Hong^3,*

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 831-848, 2022, DOI:10.32604/cmc.2022.029576 - 18 May 2022

Abstract This paper presents a parallel method for simulating real-time 3D deformable objects using the volume preservation mass-spring system method on tetrahedron meshes. In general, the conventional mass-spring system is manipulated as a force-driven method because it is fast, simple to implement, and the parameters can be controlled. However, the springs in traditional mass-spring system can be excessively elongated which cause severe stability and robustness issues that lead to shape restoring, simulation blow-up, and huge volume loss of the deformable object. In addition, traditional method that uses a serial process of the central processing unit (CPU)… More >

Liang Xie^1,2,5, Peihao Peng^1,*, Haijun Wang^1,3, Shengbin Chen⁴

Phyton-International Journal of Experimental Botany, Vol.91, No.9, pp. 2069-2086, 2022, DOI:10.32604/phyton.2022.018807 - 13 May 2022

Abstract Identifying the ecological environment suitable for the growth of Thuja sutchuenensis and predicting other potential distribution areas are essential to protect this endangered species. After selecting 24 environmental factors that could affect the distribution of T. sutchuenensis, including climate, topography, soil and Normalized Difference Vegetation Index (NDVI), we adopted the Random Forest-MaxEnt integrated model to analyze our data. Based on the Random Forest study, the contribution of the mean temperature of the warmest quarter, mean temperature of the coldest quarter, annual mean temperature and mean temperature of the driest quarter was large. Based on MaxEnt model prediction… More >

Jingkang Zhang¹, Shiyuan Zhang¹, Changhao Niu^1,2, Jiang Jiang^1,2, Haijun Sun^1,2,*

Phyton-International Journal of Experimental Botany, Vol.91, No.8, pp. 1601-1616, 2022, DOI:10.32604/phyton.2022.020323 - 14 April 2022

Abstract Soil degradation threatens the forest sustainable productivity, particularly in afforestation system. Biochar derived from agroforestry waste or biomass can potentially improve the degraded forest soil and promote the tree growth. To expand the application of biochar for forestry productivity improvement, we here reviewed the effects and the underlying mechanisms of biochar on the degraded forest soil and tree growth. Totally 96 studies that conducted from pot to field investigations in China were summarized. The result suggested that biochar generally exerted positive effects on restoration of degraded forest soil such as that with compaction, acidification or More >

Wenyuan Jin¹, Jialing Miao², Yuanfang Zhan^3,*

International Journal of Mental Health Promotion, Vol.24, No.1, pp. 1-12, 2022, DOI:10.32604/IJMHP.2022.018624 - 20 December 2021

Abstract Despite limited studies have found the negative relationships between calling and mental health symptoms, its underlying mechanism is still unknown. Drawing on the conservation of resources theory (COR), this study developed the resources model that explains the relationships between career calling, anxiety and depression, and the underlying mechanism. With a sample of 628 employees from the two-wave survey, the theorized model was tested. The results showed that career calling was able to decrease the levels of employees’ anxiety and depression, and two important resources (i.e., personal growth, and meaningful work) provided explanatory mechanisms for the More >