Intelligent Decision-Making Systems In Smart Greenhouses,
2025
Tashkent State Technical University named after Islam Karimov, 100095, Tashkent, Uzbekistan. E-mail: [email protected].
Intelligent Decision-Making Systems In Smart Greenhouses, Muso Berdiyor Ugli Allanov
Chemical Technology, Control and Management
Smart greenhouses offer a solution to sustainable food production under climate uncertainty, yet their management often depends on fixed rules or human intuition. This study proposes an intelligent decision-making framework that integrates optimization, simulation, and a neural set into a self-learning system. By generating “conditionally real data” through simulation and evolutionary algorithms, the system can predict microclimatic changes and optimize control of water, energy, and nutrients. Continuous digital feedback enables adaptive, data-efficient operation even with limited real data. Experimental results demonstrate reduced resource use and improved yield stability, advancing the development of autonomous and resilient greenhouse ecosystems.
Development Of Fire Prediction And Prevention Digital System Algorithms,
2025
Tashkent state agrarian university, Tashkent, Uzbekistan. E-mail: [email protected].
Development Of Fire Prediction And Prevention Digital System Algorithms, Oybek Zokirovich Koraboshev
Chemical Technology, Control and Management
This research work is devoted to the development of algorithms for a digital system aimed at early detection, prediction and prevention of fire hazards. In the work, the process of fire hazard assessment is modeled on the basis of modern information technologies and artificial intelligence tools. The main focus is on collecting data in real time, analyzing it and creating algorithms that determine the level of danger. In the process of research, methods of data cleaning, normalization and determination of correlation between variables were used to process multidimensional data streams obtained from various sensors (temperature, smoke, gas concentration and humidity …
The Use Of Diagnostic And Restructuring Methods To Build Reliable Management Systems,
2025
Tashkent State Technical University. Address: 2 Universitet st., 100095, Tashkent city, Republic of Uzbekistan. E-mail: [email protected], Phone: +998-90-325-85-55.
The Use Of Diagnostic And Restructuring Methods To Build Reliable Management Systems, Khurshid Salim Ugli Turayev
Chemical Technology, Control and Management
This article is devoted to the applied analysis of diagnostic and restructuring methods aimed at ensuring the reliability of control systems in the event of failures. The paper considers practical implementations of diagnostic and control algorithms using a servo drive setup as an example. The results of experiments are presented, demonstrating the system's behavior under various fault conditions. A comparative analysis of the effectiveness of the proposed solutions is carried out in terms of stability and operational accuracy. The obtained data confirm the feasibility of using adaptive control structures to increase the fault tolerance of technical systems. The article concludes …
Reinforcement Learning In A Virtual World: A Study Of Ppo And Sac Within Unity Ml Agents,
2025
Azerbaijan State Oil and Industry University. Address: Azadliq Avenue 34, AZ1010, Baku, Azerbaijan E-mail: [email protected].
Reinforcement Learning In A Virtual World: A Study Of Ppo And Sac Within Unity Ml Agents, Rufat Mammadzada
Chemical Technology, Control and Management
This study explores the use of Unity3D as a versatile platform for developing, training, and evaluating intelligent agents through reinforcement learning. Leveraging the Unity ML-Agents Toolkit, a dynamic 3D environment was created to examine agent learning behavior using two advanced algorithms: Proximal Policy Optimization (PPO) and Soft Actor-Critic (SAC). The simulation environment consisted of navigable terrain bounded by red borders, with collectible blue balls serving as rewards and a purple cube representing the agent. A carefully designed reward system was implemented to encourage goal-directed behavior and penalize inefficiency, while time constraints introduced an additional challenge requiring both precision and speed. …
Meshless Discrete Velocity Boltzmann Model For Porous Media Flow,
2025
Embry-Riddle Aeronautical University
Meshless Discrete Velocity Boltzmann Model For Porous Media Flow, Amandine Maidenberg
Doctoral Dissertations and Master's Theses
This dissertation explores the combination of two sophisticated techniques for addressing computational fluid dynamics: the discrete velocity Boltzmann equation (DVBE) and the localized collocation meshless model with upwinding (U-LCMM). The DVBE is a high-level model that describes the foundations of transport phenomena by addressing the microscale motions of particles themselves and the effect of their aggregate behaviors on continuum principles. This equation integrates multiple scales of phenomena; while it can be used for fluid flow at Navier-Stokes scales, it can also resolve fine features that can only be described at the molecular level. This type of model is necessary for …
Application Of Neural Networks For Intelligent Processing Of Sensor Signals In The Control Of Technological Process Parameters,
2025
Tashkent State Technical University, Address: 100095, Tashkent city, st. University 2, Republic of Uzbekistan.
Application Of Neural Networks For Intelligent Processing Of Sensor Signals In The Control Of Technological Process Parameters, N.R. Yusupbekov, Yu.Sh. Avazov, G.Kh. Rashidov
Chemical Technology, Control and Management
This scientific article investigates the problem of analyzing technological process parameters in the fields of chemistry, energy, and metallurgy based on sensor data and applying intelligent signal processing methods. The main objective is to evaluate the effectiveness of artificial intelligence and deep learning models for intelligent analysis, forecasting, and anomaly detection of data obtained from sensors. Time-series data collected from industrial sensors were analyzed using LSTM (Long Short-Term Memory) and Autoencoder neural networks, as well as the Kalman filter. At the first stage of the study, sensor signals were denoised and their true state was estimated using the Kalman filter. …
Modeling Of Urea Drying And Granulation Process In Fluidized Bed,
2025
Doctor of Technical Sciences, Professor of "Automation of Production Processes" Chair, Tashkent State Technical University. Adress: Uzbekistan, Tashkent city, University street 2. Phone: +998946042380;
Modeling Of Urea Drying And Granulation Process In Fluidized Bed, Jalolitdin Pakhritdinovich Mukhitdinov, Aleksey Viktorovich Schulz
Chemical Technology, Control and Management
This article is devoted to the mathematical modeling of urea drying and granulation processes in a fluidized bed. A brief description is provided for the functional blocks included in the mathematical model, along with the required parameters that form an integrated representation of the technological process. The SR-POLAR model is used to describe a phase equilibrium between the components involved. The interconnections between functional blocks are shown in the process flow diagram. Block diagrams for modeling a multi-chamber granulation unit and the cooling system for the resulting granules are presented. Granule growth in the fluidized bed is described using a …
Algorithms For Assessing Soil Salinity Levels Based On Remote Sensing Imagery,
2025
Andijan State University named after Zahiriddin Muhammad Babur, Andijan, Uzbekistan E-mail: [email protected].
Algorithms For Assessing Soil Salinity Levels Based On Remote Sensing Imagery, Bobomurod Mamitjonovich Tojiboev
Chemical Technology, Control and Management
This article investigates methods for assessing soil salinity levels based on satellite (remote sensing) imagery and their calculation algorithms. Determining the degree of salinity plays a crucial role in the rational use of land resources and increasing agricultural efficiency. The study analyzes indices for determining soil salt content using remote sensing technologies, particularly multispectral images obtained from satellite systems such as Landsat and Sentinel (for example, SI - Salinity Index, NDVI - Normalized Difference Vegetation Index, and others). Furthermore, algorithms are developed based on these indices that enable automatic determination of salinity assessments. Artificial intelligence, machine learning, and geographic information …
Research And Development Of Intelligent Measurement Systems,
2025
Navoi State University of Mining and Technology. Addres: 210100, Navoi region, Navoi, Street Galaba, 27.
Research And Development Of Intelligent Measurement Systems, Odil Abdujalilovich Jumaev, Mahmudov Giyosjon Baqoyevich
Chemical Technology, Control and Management
The article discusses modern methods for developing intelligent measuring systems. Intelligent measuring systems are systems based on intelligent technologies that not only accurately measure physical or chemical quantities, but also have the ability to self-analyze, diagnose and make management decisions. The article comprehensively examines the architecture, components of such systems, the organization of their software and hardware, the relationship of sensors and artificial intelligence algorithms. It also analyzes the practical application and prospects of intelligent measuring systems in such areas as industry, medicine, energy, ecology, transport.
Modern Methods Of Self-Monitoring, Diagnostics, And Fault Tolerance In Flow Measurement Systems,
2025
Tashkent State Technical University, Address: 2 Universitetskaya st., 100095, Tashkent city, Republic of Uzbekistan. E-mail: [email protected], Phone: +998901092908.
Modern Methods Of Self-Monitoring, Diagnostics, And Fault Tolerance In Flow Measurement Systems, Elbek Ortiqov
Chemical Technology, Control and Management
This article investigates various methods and tools for self-monitoring and fault tolerance in flow measurement transducers used in industrial processes. The study focuses on key techniques such as the use of redundancy, generation of reference values, analysis of measurement signals, and control of disturbance variables. These methods allow transducers to detect potential faults, ensure reliable operation, and maintain measurement accuracy even under adverse conditions. The article highlights how self-monitoring contributes to improving system safety, increasing reliability, and reducing downtime. It also discusses the integration of intelligent monitoring systems that support predictive maintenance and real-time diagnostics. Fault-tolerant sensors with self-monitoring capabilities …
Increasing The Robustness Of A Control System For A Complex Dynamic Plant By Correcting Nonlinearity In The Warping Process,
2025
Tashkent institute of textile and light industry
Increasing The Robustness Of A Control System For A Complex Dynamic Plant By Correcting Nonlinearity In The Warping Process, Tukhtamurod Khayitmurodovich Avezov, Zokhid Ergashboyevich Iskandarov
Chemical Technology, Control and Management
The paper discusses the challenges of enhancing the robustness of a control system for a complex dynamic plant by addressing nonlinearity in the warping process. Devices that ensure the stability of the control system against parameter non-stationarity on the warping machine are referred to as state controllers. The operating principle of these devices relies on providing artificial nonlinearity to the rear connection circuit of the control system's actuator. However, this nonlinearity is implemented using components that consider the parameters of low control quality. Therefore, it is necessary to continuously adjust the nonlinearity parameters to, on one hand, reduce the load …
Evaluation Of Deep Learning Techniques In Road Sign Recognition,
2025
Azerbaijan State Oil and Industry University. Address: Azadliq Avenue 34, AZ1010, Baku, Azerbaijan. E-mail: [email protected];
Evaluation Of Deep Learning Techniques In Road Sign Recognition, Latafat Abbas Gardashova, Haji Fakhraddin Hajiyev
Chemical Technology, Control and Management
Deep learning has transformed the computer vision field and greatly improved the performance and efficiency of road sign recognition systems. This research compares different deep learning methods, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and hybrid models, in terms of their ability to effectively detect and classify road signs under various conditions. The study compares performance measures such as accuracy, processing speed, and robustness to environmental conditions like low lighting, occlusion, and adverse weather. The results show that CNN-based methods, especially those with transfer learning and ensemble techniques, have better performance in real-time scenarios. Problems like computational …
Finding The Shortest And Optimal Path With Metaheuristic And Madm Methods,
2025
Azarbaijan State Oil and Industry University. Adress: Azadliq Avenue, 34, Baku city, Republic of Azerbaijan. E-mail: [email protected], Phone:+994-51-706-45-25.
Finding The Shortest And Optimal Path With Metaheuristic And Madm Methods, Narmin Ibrahim Hasanli
Chemical Technology, Control and Management
The article had described a method for finding the shortest and most optimal path among cities. The data had been taken from the TSPLIB library, which had provided standard examples for the Traveling Salesman Problem. This approach had integrated the advantages of the meta-heuristic technique and the Multi Attribute Decision Making method to solve the problem effectively. In the first stage, the population based meta-heuristic method ACO (Ant Colony Optimization) had found optimal solutions in large search spaces. The use of pheromone trails, heuristic information and an iterative search process had given the opportunity to find the best or near-best …
Upcycling Waste To Wealth: Cuo-Sio₂/Reduced Graphene Nanocomposite From Pomegranate Peels For One-Pot Low-Temperature Conversion Of Waste Oils Into Valuable Fatty Acid Monomers,
2025
The British University in Egypt
Upcycling Waste To Wealth: Cuo-Sio₂/Reduced Graphene Nanocomposite From Pomegranate Peels For One-Pot Low-Temperature Conversion Of Waste Oils Into Valuable Fatty Acid Monomers, Attia Attia, Shahenda Mahran Dr., Maria Centeno Prof., Basudeb Saha
Petroleum Engineering and Gas
and hence reduce the price of the fatty acid monomers. This study reports for the first time a novel, environmentally benign, highly active copper oxide-silica oxide/reduced graphene oxide (CuO-SiO2/RGO), heterogeneous nano-catalyst derived from waste pomegranate peels, for the one-pot, low-temperature synthesis of fatty acid monomers from high-acid-value waste vegetable oil (WVO). The synthesised nano-catalyst was extensively characterised using XRD, FT-IR, TEM, SEM, EDX and TGA-DTA. Further, it was utilised to synthesise fatty acidrich oleic phenoxypropyl acrylate (OPA) monomer from high acid value WVO via a single-step reaction.
Theoretical And Experimental Investigation Of Liquid-Liquid Phase Separation: Characterizing Elastin-Like-Polypeptides,
2025
University of New Mexico
Theoretical And Experimental Investigation Of Liquid-Liquid Phase Separation: Characterizing Elastin-Like-Polypeptides, Adam D. Quintana
Chemical and Biological Engineering ETDs
This dissertation develops and validates a semi-empirical Flory–Huggins-based interaction model, combined with Cahn–Hilliard simulations, for predicting multi-component liquid–liquid phase separation (LLPS) in elastin-like polypeptide (ELP) systems. Equilibrium droplet compositions, measured using a PDMS-based microfluidic device, enabled direct parameterization of interaction coefficients. The model was applied to generate phase diagrams and assess composition dependence in ternary mixtures. Cahn–Hilliard simulations were conducted to explore potential phase morphologies under different interfacial conditions. Multi-component Lattice Boltzmann simulations were implemented to model droplet morphology evolution under varying interfacial and diffusive parameters, reproducing experimentally relevant morphologies. A three-phase wetting study revealed conditions for selective wetting and …
A Smart System For Detecting Anatomic And Histological Symptoms Of Diseased Agricultural Plants,
2025
“Tashkent Institute of Irrigation and Agricultural Mechanization Engineers” National Research University, Kary Niyaziy Str., 39, 100000, Tashkent, Uzbekistan. E-mail: [email protected];
A Smart System For Detecting Anatomic And Histological Symptoms Of Diseased Agricultural Plants, Rustam Baratov, Himola Sunnatillayeva, Alimardon Mamatovich Mustafoqulov
Chemical Technology, Control and Management
This study describes a novel agricultural plant disease detecting smart system, capable of handling measured plant body parameters and images received by high resolution camera at the same time. The proposed plant disease detection method is based on evaluation of the signals received by measured and controlled plant body physical parameters like resistance, temperature and capacitance of the plant stem and image processing. An analogue plant model based on an electrical circuit with distributed parameters was developed. In addition, in the article the block diagram of the smart system for the early detection of plant diseases, the circuit diagram, its …
Modeling Of Carbonization And Absorption Processes In Soda Ash Production,
2025
Tashkent state technical university. Adress: Uzbekistan, Tashkent city, University street 2. E-mail: [email protected];
Modeling Of Carbonization And Absorption Processes In Soda Ash Production, Nadirbek Rustambekovich Yusupbekov, Djalolitdin Paxritdinovich Mukhitdinov, Fatima Faxritdinovna Iskhakova
Chemical Technology, Control and Management
The article considers the problem of modeling the ammonia-soda process of soda ash production and presents the chemistry of sodium bicarbonate (NaHCO₃) formation. The equation of the kinetics of the reaction, used as a model of the carbonation process, is derived from a system of equations and its computer model is compiled. The system of differential equations reflecting the kinetics of the process was solved in the Mathcad package. The result of the modeling is presented. Based on the experimental data, the dependence of the absorption column performance on temperature and the dependence reflecting the optimal value of the absorption …
Design Of Automation For The Absorption Process In Hydrogen Purification From Carbon Dioxide,
2025
Tashkent State Technical University. Address: 2 Universitetskaya st., 100095, Tashkent city, Republic of Uzbekistan. E-mail: [email protected], Phone:+ 998-98-304-19-51;
Design Of Automation For The Absorption Process In Hydrogen Purification From Carbon Dioxide, Azizbek Nodirbekovich Yusupbekov, Saidamirkhon Oripov, Diyoraxon Zokirxon Qizi Oripova
Chemical Technology, Control and Management
This article discusses the automation of the methanol-acetone mixture absorption process to improve control efficiency. The existing local automatic control system (ACS) was upgraded to a cascade system, reducing component concentration deviations by 12% and decreasing the transition process time from 1606 to 1592 seconds. A mathematical model of the gas absorption process was developed, incorporating material balance equations, mass transfer equations, and transfer functions. The parameters of the PI controller were calculated to ensure system stability under ±10% coefficient variations. A comparative analysis of system characteristics before and after modernization confirmed a reduction in overshoot to 0% and an …
The Importance Of The Analog-To-Digital Converter In The Measurement System,
2025
Tashkent State Transport University, Tashkent, Uzbekistan. Adilxujaev 1 str. E-mail: [email protected];
The Importance Of The Analog-To-Digital Converter In The Measurement System, Aliev Ravshan, Anvar Djalilov
Chemical Technology, Control and Management
At the moment, many scientific researches are being conducted all over the world on the economical use of water and energy resources. Most of the scientific research works are aimed at improving measurement techniques and technologies, that is, increasing their accuracy. With this in mind, a high-precision analog-to-digital converter due to its unique metrological and technical characteristics was studied in this research paper. As a result of the study, it became clear that the use of a small-sized, high-precision sigma-delta analog-to-digital converter in modern measuring technology has a positive effect on its accurate and efficient operation.
Energy Conversion In Nuclear Batteries,
2025
Tashkent State Technical Unversity. Address: 2 Universitetskaya st., 100095, Tashkent city, Republic of Uzbekistan. E-mail: [email protected], Phone: +998-94-673-11-85.
Energy Conversion In Nuclear Batteries, Suhrob Vahob O'G'Li Ibrohimov
Chemical Technology, Control and Management
The transformation of energy in nuclear reactors or processes involves converting mass into energy as a result of nuclear reactions. This can include nuclear fission (splitting heavy atomic nuclei) or nuclear fusion (combining light nuclei). In these processes, energy is released in the form of heat, which can be used for electricity generation or other purposes.
