Input Intensity Research Articles

Interpolation-based, minimum-time piecewise constant control of linear continuous-time SISO systems

We present a novel approach to the system inversion problem for linear, scalar (i.e. single-input, single-output, or SISO) plants. The problem is formulated as a constrained optimization program, whose objective function is the transition time between the initial and the final values of the system’s output, and the constraints are (i) a threshold on the input intensity and (ii) the requirement that the system’s output interpolates a given set of points. The system’s input is assumed to be a piecewise constant signal. It is formally proved that, in this frame, the input intensity is a decreasing function of the transition time. This result lets us to propose an algorithm that, by a bisection search, finds the optimal transition time for the given constraints. The algorithm is purely algebraic, and it does not require the system to be minimum phase or nonhyperbolic. It can deal with time-varying systems too, although in this case it has to be viewed as a heuristic technique, and it can be used as well in a model-free approach. Numerical simulations are reported that illustrate its performance. Finally, an application to a mobile robotics problem is presented, where, using a linearizing pre-controller, we show that the proposed approach can be applied also to nonlinear problems.

The role of defects on the transition from saturable absorption to nonlinear absorption of Bi12GeO20 single crystal under increasing laser excitation

This work reports defect and input intensity dependent nonlinear optical behaviors of Bi12GeO20 (BGO) single crystal. Open aperture (OA) Z-scan experiments were performed with 532 nm excitation wavelength under 4 ns and 100 fs pulsed laser irradiation. Obtained data were fitted with a theoretical model considering one-photon, two-photon and free carrier absorption contributions to nonlinear absorption due to longer lifetime of localized defect states than that of used laser pulse durations. At low input intensities, the BGO single crystal showed saturable absorption (SA) behavior and transition to nonlinear absorption (NA) behavior observed with further increase of the input intensities both of pulse durations. At low input intensity, the OPA mechanism is dominant and results in SA by filling of the defect states due to defect state at around one photon energy (2.32 eV). At higher input intensity, multi-photon, two-photon and free carrier absorption become dominant mechanisms, and nonlinear absorption behavior was observed. The lowest saturation threshold was found as 1.36 × 1010 W/cm2 with nanosecond pulses. We have revealed the mechanisms contributing both SA and NA, and determined saturation intensity threshold and effective nonlinear absorption coefficients. Our findings indicate that the tails of defect states overlap in the energy band gaps especially in sufficiently disordered crystal. With this way, the spectral range for saturable absorption and nonlinear absorption can be broadened.

Parallel trapping of multiple nanoparticles using a quasi-bound state in the continuum mode

In this work, we put forward an all-dielectric nanotweezer using a quasi-bound state in the continuum (quasi-BIC) mode to trap nanoparticles with a radius of 10 nm. The quasi-BIC mode provides not only a very high electric field enhancement but also a high quality factor ( Q -factor), which gives it potential for the trapping of nanoparticles with low laser power and high stability. The simulation results show that when the input intensity is 1 m W / µ m 2 , the maximum optical trapping force of the 10 nm particles is 2.24 pN, and the maximum trapping potential is 29.08 k B T . Furthermore, the proposed nanotweezer array provides multiple optical hotspots with high field confinement and enhancement, resulting in multiple trapping sites for the parallel trapping of multiple nanoparticles. The high-throughput trapping of nanoparticles provides a good foundation for studying biological cells and protein molecules, especially for the heterogeneity of cells and the large-scale parallel analyses of basic drugs.

Supply-side drivers of phosphorus emissions from phosphorus supply chains in China

ABSTRACT Human activities interfere with natural Phosphorus (P) cycles by introducing increased levels of P emissions to air, land, and water. A supply-side analysis of P supply chains and associated P emissions can provide insights into underlying economic activities and transitions responsible for human-induced P emissions. Taking the mainland China as the case, this study constructs time-series physical input-output tables to describe P supply chains during 1949–2012. Subsequently, it identifies critical products and influencing factors of P supply chains enabling P emissions to the environment (including air, land, and water) from the supply perspective. The results show that phosphate rock, an important initial supplier of P from natural environment to China’s P supply chain, was responsible for 86% of P emissions in 2012. Moreover, food crops and livestock are important initial suppliers of P from soil to China’s P supply chain, through cultivation and pasturing, respectively. From 1949 to 2012, the change in primary input level was the largest driver of P emission increments, followed by changes in population, emission intensity, and primary input structure. On the contrary, changes in production structure reduced P emissions. These findings could support supply-side policy decisions on P emission control.

Seismic response mechanisms of casing-shape composite tunnel lining: Theoretical analysis and shaking table test verification

In high-intensity seismic zones tunnel lining is generally utilized to provide efficient protection against tunnel collapse by withstanding pressure under strong earthquake events. However, this can be a challenging task in the case of fault-crossing tunnels, since tunnel lining follows the deformation of surrounding rock. To address this issue, the casing-shape tunnel lining system is proposed to reduce the constraint effects of surrounding rock on the lining structure by using an internal and external lining with a buffer layer employed in between. This research aims to investigate the rock-structure interaction and seismic response mechanism of casing-shape tunnels, both theoretically and experimentally, to facilitate the adoption of the proposed system. To develop a practical mechanical model for parametric study, the casing-shape tunnel lining is simplified as a Timoshenko composite beam. The theoretical analysis results indicate that the external lining and buffer layer can effectively reduce the earthquake-induced internal forces on the internal lining and there is an optimal length of casing-shape lining to balance cost-effectiveness with seismic resistance protection. To validate the proposed simplified model of casing-shape tunnel lining, a series of shaking table model tests are then performed on large-scale casing-shape lining models with earthquake-induced fault slippage under incremental input intensity excitations. The results demonstrate that: (i) the inclined angle of fault considerably affects the adopted length of casing-shape tunnel lining, (ii) the fault slippage shears the external lining directly leading to severe seismic damage at arch springing and invert, and (iii) the upper part of external lining and the whole internal lining generally exhibit a satisfying level of protection. This highlights the need to select appropriate cross-section shapes and structural materials for the construction of casing-shape tunnel lining systems. The outcomes of this study can provide theoretical foundation and experimental evidence for the seismic response mechanisms of casing-shape tunnel lining in practical applications.

Ultra-fast tunable optoelectronic full-adder based on photonic crystal ring resonators covered by graphene nanoshells

This paper reports a novel design of a tunable optoelectronic full-adder using two photonic crystal ring resonators (PCRRs). Every PCRR consists of a matrix of silicon rods surrounded by silica rods coated with graphene nanoshells (GNSs). The proposed full-adder is formed by three input ports, two PCRRs, and two output ports for ‘SUM’ and ‘CARRY’. The plane wave expansion technique is used to study the photonic band structure of the fundamental photonic crystal (PhC) microstructure, and the finite-difference time-domain method is also employed in the final design for solving Maxwell's equations to analyze the light propagation inside the structure. We can tune the PhC resonant mode for our desired application by setting the chemical potential of GNSs with an appropriate gate voltage. The numerical results reveal that when the chemical potential of GNSs changes, the switching mechanism occurs and manages the coupling and propagation direction of the input beam inside the structure. We systematically study the effects of physical parameters on the transmission, reflection, and absorption spectra . Our numerical results also demonstrate that the maximum delay is about 0.8 ps. The 663 μm 2 area of the proposed full-adder based on two-dimensional materials makes it a building block of every photonic integrated circuit used for data processing systems. • A fast and compact all-optical full-adder using photonic crystal ring resonators (PCRRs). • A maximum steady-state time of about 0.8 ps and the structure's total size of 663 μm 2 . • There is no need to increase the input intensity for the appearance of the nonlinear effect. • The ON-OFF contrast ratios for Sum and Carry are 16 dB and 14 dB, respectively. • The full-adder is applicable in optical integrated circuits for high-speed signal processing.

Assessing the eco-efficiency of complex forestry enterprises using LCA/time-series DEA methodology

Complex forestry enterprises have the potential to lead the current industrial upgrade under the strategy of carbon neutrality and carbon peaking. This paper aims to investigate the inputs and outputs influencing the eco-efficiency of complex forestry enterprises through a case study. A hybrid ensemble approach of life cycle assessment (LCA) and time-series data envelopment analysis (time-series DEA) was proposed to evaluate the case enterprise's eco-efficiency. It is found that, from the perspective of the average intensity of key input and output factors, environmental impact in efficient years is 45.25% of that in inefficient ones, and when it comes to the fiber consumption and the energy consumption, this percentage turns into 65.53% and 77.66%. With the findings, we provide guidelines for complex forestry enterprises to enhance the eco-efficiency in improving environmental impact and in giving full play to the advantages of forestry industrial chain resources. Our findings also contribute to the existent literature by providing a systematic study based on a corporate time-series dataset.

Deterministic Light-to-Voltage Conversion with a Tunable Two-Dimensional Diode.

Heterojunctions accompanied by energy barriers are of significant importance in two-dimensional materials-based electronics and optoelectronics. They provide more functional device performance, compared with their counterparts with uniform channels. Multimodal optoelectronic devices could be accomplished by elaborately designing band diagrams and architectures of the two-dimensional junctions. Here, we demonstrate deterministic light-to-voltage conversion based on strong dielectric screening effect in a tunable two-dimensional Schottky diode based on semiconductor/metal heterostructure, where the resultant photovoltage is dependent on the intensity of light input but independent of gate voltage. The converted photovoltage across the diode is independent of gate voltage under both monochromatic laser and white light illumination. In addition, the Fermi level of two-dimensional semiconductor area on dielectric SiO2 is highly gate-dependent, leading to the tunable rectifying effect of this heterostructure, which corporates a vertical Schottky junction and a lateral homojunction. As a result, a constant open-circuit voltage of ∼0.44 V and a hybrid “photovoltaic + photoconduction” photoresponse behavior are observed under 1 μW illumination of 403 nm laser, in addition to an electrical rectification ratio up to nearly 104. The scanning photocurrent mappings under different bias voltages indicate that the switchable operation mode (photovoltaic, photoconduction, or hybrid) depends on the bias-dependent effective energy barrier at the two-dimensional semiconductor–metal interface. This approach provides a facile and reliable solution for deterministic on-chip light-to-voltage conversion and optical-to-electrical interconnects.

Effects of human tissue acoustic properties, abdominal wall shape, and respiratory motion on ultrasound-mediated hyperthermia for targeted drug delivery to pancreatic tumors

Background PanDox is a Phase-1 trial of chemotherapeutic drug delivery to pancreatic tumors using ultrasound-mediated hyperthermia to release doxorubicin from thermally sensitive liposomes. This report describes trial-related hyperthermia simulations featuring: (i) new ultrasonic properties of human pancreatic tissues, (ii) abdomen deflections imposed by a water balloon, and (iii) respiration-driven organ motion. Methods Pancreas heating simulations were carried out using three patient body models. Pancreas acoustic properties were varied between values found in the literature and those determined from our human tissue study. Acoustic beam distortion was assessed with and without balloon-induced abdomen deformation. Target heating was assessed for static, normal respiratory, and jet-ventilation-controlled pancreas motion. Results Human pancreatic tumor attenuation is 63% of the literature values, so that pancreas treatments require commensurately higher input intensity to achieve adequate hyperthermia. Abdominal wall deformation decreased the peak field pressure by as much as 3.5 dB and refracted the focal spot by as much as 4.5 mm. These effects were thermally counteracted by sidelobe power deposition, so the net impact on achieving mild hyperthermia was small. Respiratory motion during moving beam hyperthermia produced localized regions overheated by more than 8.0 °C above the 4.0 °C volumetric goal. The use of jet ventilation reduced this excess to 0.7 °C and yielded temperature field uniformity that was nearly identical to having no respiratory motion. Conclusion Realistic modeling of the ultrasonic propagation environment is critical to achieving adequate mild hyperthermia without the use of real time thermometry for targeted drug delivery in pancreatic cancer patients.

Clay stratigraphy of the Lambeth Group of borehole IOD8R

The clay mineralogy of the Lambeth Group is shown to be highly variable, demonstrating a strong correlation with palaeoenvironment. The principal causes of this variability are changes in intensity of contemporaneous weathering (pedogenesis) and possible input of volcanic tephra. Previous studies have suggested that smectite is the dominant clay throughout the Lambeth Group in the London Basin, but we show that this is not the case in borehole IOD8R. Absolute clay mineral abundances are also highly variable, reflecting changes in sediment grain size and environment of deposition. The engineering properties of the Lambeth Group are largely controlled by the distribution of clay minerals, and in particular, the abundance of smectite. The data we present for borehole IOD8R illustrate the importance of assessing the scale of variability of such factors as swelling clay abundance when planning and supervising a site investigation.

Sensitivity-based constitutive parameter identification of nonlinear structures with unknown input earthquake excitation

System identification methods are widely developed in structural health monitoring, in which the force or structural damage is identified from a linearised structure. However, the real-world civil infrastructures are generically nonlinear and subject to extreme loading conditions, such as earthquake. This study proposes a system identification method for material constitutive nonlinear structures subject to earthquake, where sensitivity analysis is developed to accelerate the complicated nonlinear system identification. First, the nonlinear structural model based on the material constitutional law is constructed by fiber beam-column elements. The earthquake input is parameterized by Chebyshev orthogonal polynomials in a recognizable form. Afterwards, the dynamic response sensitivities with respect to the constitutive parameters and the orthogonal factors of earthquake excitation are derived to accelerate the system identification from a complex material constitutive model. Finally, the constitutive parameters and the earthquake input are simultaneously identified by an optimization process. Numerical structures subjected to earthquake excitation are employed to verify the accuracy of the proposed method, by which the influence of parameter's order, input intensity and measurement noise is discussed. The proposed method develops Chebyshev parameterization to recognize the earthquake input and sensitivity analysis to accelerate the optimization, which leads to an accurate nonlinear system identification of civil structures.

Application of Chemical Sequence Stratigraphy to the Prediction of Shale Gas Sweet Spots in the Wufeng and Lower Longmaxi Formations within the Upper Yangtze Region

Effective shale gas exploration is hindered by the need for obtaining high-resolution correlations between shale strata and the need for classifying shale facies. To address these issues, chemostratigraphy, sequence stratigraphy, and shale gas geology methods were integrated to develop a new method known as “chemical sequence stratigraphy,” which was successfully applied to the Wufeng–Lower Longmaxi Formations in the upper Yangtze region. Well Huadi 1 was used as a case study, and detailed data were acquired. Multivariate statistical analyses were applied to three defined indices having different genetic significance, namely: terrigenous input intensity (TII), authigenic precipitation intensity (API), and organic matter adsorption and reduction intensity (OARI). By analyzing the trends of these three indices, the Wufeng–Lower Longmaxi Formations were divided into five fourth-order chemical sequences (from bottom to top): LCW, MCL1-1, MCL1-2, MCL1-3, and MCL1-4. The geochemical facies were named and classified using the chemical sequence stratigraphic framework. The enrichment factor (EF) transformation of elements was conducted to determine whether an element is rich or deficient. The results showed that the favorable geochemical facies in the well were EF-Al deficient, EF-Ca rich, and EF-V rich. The organic matter content and rock brittle strength were then used as chemical parameters, and it was predicted that the LCW and MCL1-1 chemical sequences most likely comprised shale gas sweet spots. This conclusion is consistent with the drilling results and indicates that our proposed method is effective and reliable. This method is further applied to the Changning Shuanghe section, the Shizhu Liutang section, and sections in the Xindi 1 well in the upper Yangtze region. The comparative study of these four sections showed that LCW and MCL1-1 are the key chemical sequences for shale gas exploration and development in the Wufeng–Lower Longmaxi Formations within the Upper Yangtze region.

Multistability in Coupled Nonlinear Metasurfaces

Multistability, namely, the property of obtaining different outputs depending on the past values of the input, is the key effect behind memory components in a variety of electronic, chemical, biological, and quantum systems. Two electromagnetic metasurfaces, with nonlinear admittances of Kerr type, are found to manifest significant multistability regarding their transmissivity. Such a feature is owed to the discontinuous variation of the response once the nature of the material changes from dielectric to plasmonic and vice versa, occurring at different levels of incoming power. The conditions for giving sizable hysteresis loops, with respect to either the input intensity or its operational wavelength, are determined. The reported results are expected to assist the modeling of nonlinear metasurfaces and open unexplored opportunities toward the efficient design of photonic memory elements.

Tackling climate risk to sustainably intensify smallholder maize farming systems in southern Africa

Sustainable intensification (SI) of low input farming systems is promoted as a strategy to improve smallholder farmer food security in southern Africa. Using the Limpopo province South Africa as a case study (four villages across a climate gradient), we combined survey data (140 households) and quantitative agronomic observations to understand climate-induced limitations for SI of maize-based smallholder systems. Insights were used to benchmark the agroecosystem model Agricultural Production System sIMulator, which was setup to ex ante evaluate technology packages (TPs) over 21-seasons (1998–2019): TP0 status quo (no input, broadcast sowing), TP1 fertiliser (micro dosing), TP2 planting density (recommended), TP3 weeding (all removed), TP4 irrigation, TP5 planting date (early, recommended), and TP6 all combined (TPs 1–5). An additional TP7 (forecasting) investigated varying planting density and fertiliser in line with weather forecasts. Input intensity levels were low and villages expressed similar challenges to climate risk adaptation, with strategies mostly limited to adjusted planting dates and densities, with less than 2% of farmers having access to water for irrigation. Simulations showed that combining all management interventions would be expected to lead to the highest mean maize grain yields (3200 kg ha−1 across villages) and the lowest harvest failure risk compared to individual interventions. Likewise, simulations suggested that irrigation alone would not result in yield gains and simple agronomic adjustments in line with weather forecasts indicated that farmers could expect to turn rainfall variability into an opportunity well worth taking advantage of. Our study emphasises the need for a cropping systems approach that addresses multiple crop stresses simultaneously.

Correct path to use flumes in water resources management

The hydraulic characteristics of the flow are measured using tools such as flumes, in the design and evaluation of furrow irrigation systems. Proper use of these tools, such as their immersion while working, is one of the important executive points in this field; in this study, trapezoidal flumes are used to measure the intensity of input and output flow in furrow irrigation. The proper method of installing these flumes was investigated in this article. For this purpose, during 60 irrigation operations, the results showed that in order to create free flow conditions in these flumes, and not to affect the downstream and upstream current, as well as increasing the accuracy of measurements, in addition to installing flumes in all directions, trapezoidal flume should be installed at a height of at least about 4 cm above the furrow bed; according to the irrigation operations, the percentage of immersion in the installation of the flume at a height of 4 cm from the furrow bed was observed as standard (less than 70% immersion) in order to reduce the percentage of flow measurement error in different depths of water entering the flume. The results also showed that for ensuring free flow in trapezoidal flumes, the flume should be installed at a height of 4 cm or more above the furrow bed, provided the input ridges are strengthened and the end flume is measured to measure the inflow to the furrow. The output current of the furrow should be installed in the floor of the furrow along the bed to prevent the passage of current, provided that after the outflow flume, the furrow bed should be deeper in terms of free flow. Observance of the points and results obtained in this study in furrow irrigation systems prevents errors in flow measurement and consequently increases the accuracy in the design and evaluation of furrow irrigation systems.

Equal input, compact optical power coupler based on a nano-pixel structure designed with machine learning

A multi-mode interference (MMI) waveguide has been widely researched and developed to realize an optical power coupler. MMI coupler exhibits the superior performance of the “Equal intensity coupling” characteristics, however, it has a problem that excess loss occurs if the phase-matching condition is not satisfied at all of the input ports. The phase condition depends on the number of input ports, and relatively complicated phase control is required, thus, it is desired to realize an optical power coupler without complicated phase adjustment. In order to avoid the phase-control difficulty, a nano-pixel power coupler is investigated in this paper. The nano-pixel-based coupler has the merit of ultra-compact dimension which is close to the wavelength order, therefore, it is expected that less excess loss even under simple “equal” phase conditions. The structure was examined using FDTD and the simulated results show equal input (intensity and phase) coupling capabilities with a low excess loss of 0.11 dB.

Quantitative cerebrovascular reactivity MRI in mice using acetazolamide challenge.

To develop a quantitative MRI method to estimate cerebrovascular reactivity (CVR) in mice. We described an MRI procedure to measure cerebral vasodilatory response to acetazolamide (ACZ), a vasoactive agent previously used in human clinical imaging. Vascular response was determined by cerebral blood flow (CBF) measured with phase-contrast or pseudo-continuous arterial spin labeling MRI. Vasodilatory input intensity was determined by plasma ACZ level using high-performance liquid chromatography. We verified the source of the CVR MRI signal by comparing ACZ injection to phosphate-buffered saline injection and noninjection experiments. Dose dependence and feasibility of regional CVR measurement were also investigated. Cerebral blood flow revealed an exponential increase following intravenous ACZ injection, with a time constant of 1.62 min. In contrast, phosphate-buffered saline or noninjection exhibited a slow linear CBF increase, consistent with a gradual accumulation of anesthetic agent, isoflurane, used in this study. When comparing different ACZ doses, injections of 30, 60, 120, and 180 mg/kg yielded a linear increase in plasma ACZ concentration (p < 0.0001). On the other hand, CBF changes under these doses were not different from each other (p=0.50). The pseudo-continuous arterial spin labeling MRI with multiple postlabeling delays revealed similar vascular responses at different postlabeling delay values. There was a regional difference in CVR (p=0.005), with isocortex (0.81 ± 0.17%/[μg/ml]) showing higher CVR than deep-brain regions. Mice receiving multiple ACZ injections lived for a minimum of 6months after the study without noticeable aberrant behavior or appearance. We demonstrated the proof-of-principle of a new quantitative CVR mapping technique in mice.

Spectral Characteristics Change in Dissolved Organic Matter in Urban River Under the Influences of Different Intensities of Non-point Source Pollution

With the method of ultraviolet-visible absorption spectroscopy (UV-vis) and excitation-emission matrix spectroscopy combined with parallel factor analysis (EEMs-PARAFAC), this study analyzed the change in dissolved organic matter (DOM) content and composition in spring and summer of two non-point source urban rivers which had different input intensities. The results indicated that the level of humification and molecular weight of DOM in summer was significantly higher than that in spring in these two rivers (P<0.01). The PARAFAC model was used to analyze four chemical compositions, including C1 (UVC fulvic-like), C2 (tryptophan-like), C3 (humic-like), and C4 (UVA fulvic-like); furthermore, C1[(31±6)%] and C2[(31±4)%] were the main fluorescent contents of the water. The high non-point source input river had a higher fluorescence intensity of all four PARAFAC components in spring than in summer, contrary to the low non-point source input river. The random forest regression model showed that C3% had the highest sensitivity to the changes in water parameters (R2=0.75, P<0.001) and could be an effective indicator. Additionally, the coverage level of the water surface (Cover) had an essential effect on the prediction of C4% (P<0.001), and C4% was susceptible to photochemical oxidation. According to the principal component analysis (PCA) and Adonis test, nitrogen and phosphorus were the essential impetuses for the biological process of the river; non-point source inputs and seasonal changes had a significant impact on the urban river (R2=0.775, P<0.001). The contents and compositions of urban river DOM were affected by many essential factors. Non-point source inputs improved the input level of terrestrial humus in the water and promoted the biological process at the same time, dynamically contributing to the changes in the DOM of the water body.

Temporal and Spatial Variation Characteristics and Source Analysis of Agricultural Non-point Source Pollution Load in Guangdong During the Past 20 Years

The agricultural non-point source pollution (ANPSP) load in Guangdong province is very large and has a serious impact on the regional ecological environment. Inventory analysis was used to assess and analyze the temporal and spatial variation characteristics of the ANPSP load of Guangdong province during 1999-2019, and the sources of ANPSP were discussed, as well as the relationship between them. The results showed that, during the past 20 years, the total ANPSP pollution loads of Guangdong province decreased by 6.08%, and the pollution loads of chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) increased by -11.88%, 4.99%, and 26.17%, respectively. The input intensity of chemical fertilizers and pesticides increased by 112.19% and 60.38%, respectively. The Pearl River Delta had the highest ANPSP loads in Guangdong province, followed by those in northern, western, and eastern Guangdong. Livestock and poultry breeding were the main sources of COD, the total percent fertilizers and livestock and poultry breeding were the main sources of TN, and livestock and poultry breeding and aquaculture were the main sources of TP. In addition, the contribution of pollutants discharged from aquaculture showed an obvious increasing trend. There were certain differences in the pollution sources in different regions. In western Guangdong, northern Guangdong, and eastern Guangdong, livestock and poultry breeding were the main sources of COD and TP, and fertilizer was the main source of TN; by contrast in the Pearl River Delta, aquaculture had become the main source of TN and TP pollution loads. The correlation results showed that the decline in the total ANPSP in Guangdong province was mainly due to the increase in high urbanization rate and the decrease in the proportion of rural population. In general, there were stage changes in the time and differences in spatial characteristics and sources of ANPSP in Guangdong province. A combination of comprehensive treatment and targeted pollution treatment should be adopted, and fertilizer reduction measures and pollution treatment in the aquaculture should be strengthened in an all-around way, focusing on strengthening the treatment of pollution from aquaculture in the Pearl River Delta region and the treatment of rural life pollution in northern Guangdong.

СРАВНИТЕЛЬНАЯ ОЦЕНКА ЭФФЕКТИВНОСТИ АЛГОРИТМОВ МАШИННОГО ОБУЧЕНИЯ С ПОДКРЕПЛЕНИЕМ И ОПТИМИЗАЦИИ ПРИ УПРАВЛЕНИИ ТРАНСПОРТНЫМИ ПРОЦЕССАМИ В СРЕДЕ ANYLOGIC

The task of increasing the throughput of sections of the transport network of the metropolis with the existing infrastructure is solved by means of automated traffic control systems, the purpose of which is to form control actions on the objects of the transport system in real time. An adequate response to load changes in the transport network is implemented by controlling traffic light objects using built-in adaptive algorithms, among which artificial intelligence technologies, in particular, neural networks, are increasingly being used. The noted approaches compete with the widely used optimization-based adaptation method (phase duration, displacement, etc.). The proposed article examines the issue of comparing the efficiency of an optimization algorithm with reinforcement machine learning algorithms by the criterion of the time spent by vehicles in the intersection system in the Anylogic simulation environment. This study will help determine a more efficient solution to the problem of setting the duration of traffic light control phases. It was shown that in the reinforcement learning algorithm, the ability to adapt to input intensities within the schedule is higher compared to the optimization algorithm. However, the reinforcement algorithm is more sensitive to the type of schedule than the optimization algorithm, which outperformed the latter by about 20% at the optimal point for the weekday schedule. The advantage of the reinforcement algorithm was more pronounced on the 2nd schedule, which features a tendency to increase traffic intensity, namely: 61% compared to the optimization and 70% compared to the base setting. It turned out to be practically insensitive to the “detuning” of the input data relative to the optimal policy when changing the intensity levels within this schedule. Thus, it was shown that the results of the regulation of the traffic process at the studied real intersection, obtained by modeling using reinforcement learning, are superior to the optimization approach, but are sensitive to the given intensity schedule.