Swarm intelligence for energy-efficient heating, ventilation, and air conditioning (HVAC) systems: A case study in smart buildings by Vinoth Kanna I, Raja Subramani, Maher Ali Rusho, Shubham Sharma, Ramachandran T, Abinash Mahapatro, Deepak Gupta, Jasmina Lozanovic

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Optimization of air conditioning mechanical ventilation using simulated annealing for enhanced energy efficiency and cost reduction by Enio Pedone Bandarra Filho, Gleyzer Martins, Muhammad Bilal Riaz, Sardar Muhammad Bilal, Oscar Saul Hernandez Mendonza

“…Abstract Air conditioning systems are essential for ensuring indoor thermal comfort in commercial buildings; however, they are also significant consumers of electrical energy, contributing to increased environmental impact. …”
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Ways to improve characteristics of the climate systems of passenger rolling stock by G. M. Stoyakin, A. V. Kostin, S. N. Naumenko

“…The microclimate parameters permissible for a long stay of people (the longest route is about 6 days) are achieved by installing ventilation, air conditioning and heating systems. Currently, more and more attention is being paid to the safety and comfort of passengers, and the urgent task is to create a climate system that ensures that the air environment in the premises of passenger rolling stock is up to date with all requirements. …”
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Recent Advancements in Latent Thermal Energy Storage and Their Applications for HVAC Systems in Commercial and Residential Buildings in Europe—Analysis of Different EU Countries’ S... by Belayneh Semahegn Ayalew, Rafał Andrzejczyk

“…Heating, ventilation, and air-conditioning (HVAC) systems account for the largest share of energy consumption in European Union (EU) buildings, representing approximately 40% of the final energy use and contributing significantly to carbon emissions. …”
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Optimizing HVAC energy efficiency in low-energy buildings: a comparative analysis of reinforcement learning control strategies under Tehran climate conditions by Mohammad Anvar Adibhesami, Amir Hassanzadeh

“…This study investigates the incorporation of advanced heating, ventilation, and air conditioning (HVAC) systems with reinforcement learning (RL) control to enhance energy efficiency in low-energy buildings amid the extreme seasonal temperatures of Tehran. …”
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Keeping it Safe: Energy Conservation=More Money by Mary N. Harrison

“… Heating and cooling your home uses more energy and takes up more money than any other system in your home. No matter what kind of heating, ventilation, and air-conditioning system you have, you can save money and increase comfort by properly maintaining the equipment. …”
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河南地区浅圆仓大豆储存中不同储粮控温技术的 应用现状及展望Application status and prospects of different grain storage temperature control technologies in the storage of soybeans in squat silo... by 张慧民， 古争艳， 吴宗霖， 王彬， 马国平， 李国彬 ZHANG Huimin, GU Zhengyan, WU Zonglin, WANG Bin, MA Guoping, LI Guobin

“…Future research could be carried out in the direction of radial direction ventilation technology application in real silo, water retention and loss reduction application in humidification system, radiant refrigeration heat insulation modification, ozone and inner circulation fusion control of book lice, air conditioning and inner circulation combination for temperature control and other directions.…”
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Space Design for Thermal Comfort and Energy Efficiency in Summer by Xiaoyu Du

“…Passive cooling techniques, where solar and heating control systems are applied, largely depend on the design of the urban morphology and the building shape. …”
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A neural-network-enhanced parameter-varying framework for multi-objective model predictive control applied to buildings by Dylan Wald, Olga Doronina, Kathryn Johnson, Ryan King, Michael Sinner, Kevin Griffin, Rohit Chintala, Deepthi Vaidhynathan, Jibonananda Sanyal, Marc Day

“…In this work, we propose an advanced control method, called adaptive neural parameter-varying model predictive control (ANPV-MPC), to control the temperature and energy consumption of a building via its Heating, Ventilation, and Air Conditioning system. ANPV-MPC combines key ideas in parameter-varying control, adaptive control, and online learning strategies to bridge the gap between computationally efficient linear model predictive control and more accurate nonlinear model predictive control. …”
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