Effect Of Randomness Research Articles

Effect of spatial variation of spoil material properties on slope displacements under rapid drawndown of pit lakes

In many European countries, lignite or brown coal is used as a fuel source in steam-electric power generation. Upon completion of mining activities, a reclamation plan is imperative to ensure environmental and social prosperity of local areas. Abandoned mine pits are often reclaimed by creating a pit lake. Reclamation of large lignite open pit mine sites may use large amounts of previous overburden materials or “spoils” to create the slopes of the pit lake. Spoils are anthropogenic materials with large spatial variation in properties, hence, considering mean values of shear strength and hydraulic parameters to assess stability and seasonal displacements will not fully simulate actual field conditions. This paper considers the effect of spatial variation on slope stability and ground movements during rapid drawdown events (a critical case) using coupled flow-deformation 2D finite element analyses, incorporating unsaturated soil suctions above the phreatic surface. Effects of heterogeneity and randomness of spoils on the response of the slope are considered through random field modelling and the Monte-Carlo simulation technique. Four lognormally distributed random variables (spoil cohesion, friction angle, void ratio, and permeability coefficient) are examined. The effect of spatial variability of spoils is shown to be important; a significant number of the random field analyses resulted in larger displacements compared to a benchmark deterministic analysis adopting uniform mean parameter values.

Security Analysis of Sending or Not-Sending Twin-Field Quantum Key Distribution with Weak Randomness.

Sending-or-not sending twin-field quantum key distribution (SNS TF-QKD) has the advantage of tolerating large amounts of misalignment errors, and its key rate can exceed the linear bound of repeaterless quantum key distribution. However, the weak randomness in a practical QKD system may lower the secret key rate and limit its achievable communication distance, thus compromising its performance. In this paper, we analyze the effects of the weak randomness on the SNS TF-QKD. The numerical simulation shows that SNS TF-QKD can still have an excellent performance under the weak random condition: the secret key rate can exceed the PLOB boundary and achieve long transmission distances. Furthermore, our simulation results also show that SNS TF-QKD is more robust to the weak randomness loopholes than the BB84 protocol and the measurement-device-independent QKD (MDI-QKD). Our results emphasize that keeping the randomness of the states is significant to the protection of state preparation devices.

Effect ofRandom Mobility Models Pattern in Mobile Ad hoc Networks

Effect ofRandom Mobility Models Pattern in Mobile Ad hoc Networks

Stochastic behavior of exchange rate on an international supply chain under random energy price

Monetary policy and logistics management are two important factors for international supply chain management. Selling imported items is a little bit more difficult rather than the domestic supply chain. This paper studies this context by developing a suitable policy for trade-credit financing. The supply chain management uses the just-in-time policy to increase efficiency. An inspection process runs for all inventory to eliminate the risk of random defective rates regarding the quality of items. The vendor uses a multiple shipment policy to deliver inventory to the buyer’s end. The stochastic dollar exchange rate has importance in the international supply chain as supply chain players are situated in different countries. The vendor allows a fixed credit period for paying the wholesale price to the buyer. In the meantime, the buyer increases the sale and boosts the revenue. Environmental effects of carbon emission and randomness of energy prices are discussed within this study. Global optimality of the non-linear objective function is shown both theoretically and numerically by developing an algorithm. Sensitivity analysis has been provided based on the numerical experiment to find the changes in global minimum cost.

Vorogrid: A static‐aware variable‐density Voronoi mesh to design the tube structure tessellation of tall buildings

AbstractIn the context of tall building design, the tube concept represents one of the most performing systems. The diagrid is the widespread type of tube system and consists of a diagonal grid of beams that wraps the building, forming a diamond pattern. It performs as lateral bracing and is additionally able to sustain vertical loading through axial forces. Despite its efficiency, a growing interest is recently observed in alternative geometries to replace the diagrid pattern and improve the architectural impact conferred by the building skin aesthetics on the urban environment. The paper pursues the use of a Voronoi mesh, in which the geometry of the cells is steered to known schemes for the structural design of a cantilever tube structure. The objective is to mimic a macroscopic structural behavior through a topology and size modification of the Voronoi mesh that increases the density for creating resisting paths with higher stiffness. The paper proposes a novel method Vorogrid for designing a new class of tall buildings equipped with an organic‐looking and mechanically sound tube structure, which makes them a valuable alternative to competitors (diagrid, hexagrid, random Voronoi). Diagrids and hexagrids still remain more efficient in terms of forces and displacements but are characterized by a more usual appearance, instead Vorogrid offers more design control and better performances on average with respect to random Voronoi structures. This method is streamed into a pipeline that includes grid initialization strategies, geometric and structural optimization to mitigate the effects of the grid randomness, and structural sizing.

Delays and Queue Lengths at Traffic Signals With Two Greens in One Cycle

Under specific circumstances signal timing at a traffic signal allows the switching of two green times within one cycle. Practitioners expect a reduction in delays and queue length as a result of this control strategy. However, no analytical methodology is available to quantify this effect. To resolve this deficit, analytical considerations have been undertaken. They follow the principles that are also the basis for conventional signal performance analysis. The basic difference compared with a single green is that, within each cycle, the maximum length of the vehicle queue remains shorter under the two-green regime. This effect is expressed by the term uniform delay, w1. For that parameter, a specific deterministic derivation is proposed. The second element is the incremental delay, w2, which stands for the effects of randomness and temporary oversaturation. The analysis confirmed that this parameter could be adopted from conventional methods. Different formulas for the estimation of w2 were investigated using simulation studies. Thus, a set of equations is given for the prediction of average delay and of percentile queue length in the case of two green times. Verification of the derived formulas was performed using Monte Carlo simulations. The results could easily be applied in practice and might be implemented into guidelines. The application demonstrated how a second green within one signal cycle reduced delays and, notably, queue lengths.

Protocol for a collaborative randomised effectiveness trial of lay-delivered versus clinician-delivered behavioural activation in senior centres

IntroductionDepression is common among community-dwelling older adults who make use of senior centre services yet remains undertreated due to a lack of acceptable and available treatments. Emerging evidence suggests that...

Investigating river health and potential risks using a novel hybrid decision-making framework with multi-source data fusion in the Qinghai-Tibet Plateau

River health assessment (RHA) is a powerful tool for examining river health and provides promising solutions for ecological conservation and sustainable river management. However, currently available methods still fail to consider the superimposed effects of randomness and fuzziness on RHA. Additionally, the existing RHA studies mainly focus on the plains and lack detailed investigations in the Qinghai-Tibet Plateau (QTP). Terrain, climate, natural hazards and human activities contribute to the inherent fragility and inevitable uncertainty of rivers in the QTP. This study proposed a novel intuitionistic fuzzy cloud (IFC) by coupling the intuitionistic fuzzy sets and cloud model. A new hybrid decision-making framework based on IFC algorithm was then developed to facilitate the RHA with fuzziness and randomness. To deeply investigate river health in the QTP, the Lhasa River (LR) was chosen as a typical study area. We formulated an indicator system with multi-source data fusion, and used the geodetector technique to explore the drivers and potential risks associated with river health. Results showed that the developed research framework addressed the shortcomings of conventional techniques, expanded the capabilities of existing models, and offered a potentially promising approach to RHA with fuzziness and randomness. In LR, health statuses of evaluation indicators were unsatisfactory, with healthy compliance rates of 100%, 62.5% and 37.5% in the upper, middle and lower reaches, respectively. Meanwhile, health statuses demonstrated substantial spatial variation in LR. Excellent, healthy and subhealthy sampling sites accounted for approximately 28%, 24% and 48% of the total. Our results highlight that dam construction, urbanization and fish release have posed potential risks to the LR health, and appropriate measures should be developed immediately to mitigate their impacts on ecologically fragile areas.

Effectiveness–implementation hybrid-2 randomised trial of a collaborative Shared Care Model for Detecting Neurodevelopmental Impairments after Critical Illness in Young Children (DAISY): pilot study protocol

IntroductionIn Australia, while paediatric intensive care unit (PICU) mortality has dropped to 2.2%, one in three survivors experience long-term neurodevelopmental impairment, limiting their life-course opportunities. Unlike other high-risk paediatric populations,...

Meta-analysis on efficacy of PCI treatment or conservative treatment among patients with chronic total occlusions

Objective: To compare the efficacy between percutaneous coronary intervention (PCI) and conservative medication treatment in chronic total occlusions (CTO) patients. Methods: It was a meta-analysis.Articles on drug therapy and PCI for complete coronary artery occlusion were retrieved from Pubmed, Embase and Web of Science databases. The search time was from the database construction to May 10, 2020, and the following search criteria were used for the search "chronic total occlusion" "percutaneous coronary intervention" and "medical therapy". References from searched literatures were also searched to identify more eligible studies. Randomized controlled trials (RCT) and cohort studies comparing efficacy of PCI versus oral medication as well as medication as initial therapy option for CTO patients with single or multiple lesions were included. The primary endpoints included all-cause death, cardiac death, recurrent myocardial infarction, re-revascularization, major adverse cardiac events (MACE) and stroke. Data were analyzed with ReviewManager5.3.0 software. Pooled effect size RR and 95%CI were calculated by randomization effect model. Heterogeneity was evaluated by I2. Bege test was used to evaluate publication bias. Subgroup analyses were performed for RCT and cohort studies. Results: A total of 1 079 articles were retrieved and 16 studies (RCT=4, cohort study=12) were included with 12 223 patients. Fourteen publications (RCT=4, cohort study=10) reported all-cause death post PCI and/or drug therapy. Results showed that risk of all-cause death was significantly lower in PCI group than in drug therapy group (RR=0.45,95%CI 0.39-0.53,P<0.001);subgroup analysis showed that risk of all-cause death was significantly lower in PCI group than in drug therapy group from cohort studies (RR=0.44,95%CI 0.38-0.52,P<0.001),but comparable in RCT (P=0.27). Thirteen studies (RCT=3, cohort study=10) reported cardiac death post PCI and/or drug therapy. Results showed that risk of cardiac death was significantly lower in PCI group than in drug therapy group (RR=0.44,95%CI 0.35-0.55,P<0.001);subgroup analysis showed that risk of cardiac death was significantly lower in PCI group than in drug therapy group in cohort studies (RR=0.43,95%CI 0.34-0.54,P<0.001),but not in RCT (P=0.25). Fourteen publications (RCT=4, cohort study=10) reported recurrent myocardial infarction post PCI and/or drug therapy. Results showed that risk of recurrent myocardial infarction was significantly lower in PCI group than in drug therapy group (RR=0.62,95%CI 0.44-0.88,P=0.007);subgroup analysis showed that risk of recurrent myocardial infarction was significantly lower in PCI group than in drug therapy group from cohort studies (RR=0.56,95%CI 0.40-0.78,P=0.000 5),but comparable in RCT (P=0.17). Fourteen publications (RCT=4, cohort study=10) reported re-revascularization post PCI and/or drug therapy. Results showed that risk of re-revascularization was comparable between PCI group and drug therapy group (P=0.91);subgroup analysis showed that risk of re-revascularization was comparable between PCI group and drug therapy group both in cohort study and RCT (P=0.60 and 0.41, respectively). Eleven publications (RCT=3, cohort study=8) reported MACE post PCI and/or drug therapy. Results showed that risk of MACE was significantly lower in PCI group than in drug therapy group (RR=0.74,95%CI 0.59-0.93,P=0.03);subgroup analysis showed that risk of MACE was significantly lower in PCI group than in drug therapy group in cohort studies (RR=0.72,95%CI 0.56-0.93,P=0.01), but not in RCT (P=0.8). Six publications (RCT=2, cohort study=4) reported stroke post PCI and/or drug therapy. Results showed that risk of stroke was comparable between PCI and drug therapy groups (RR=0.62,95%CI 0.32-1.20, P=0.15);subgroup analysis showed that risk of stroke was comparable between PCI and drug therapy groups both in cohort studies and RCT (P=0.48 and 0.32, respectively). Conclusion: Compared with oral drug therapy, PCI may have better efficacy for CTO patients based on results from this cohort study.

Estimating epistemic uncertainty in soil parameters for nonlinear site response analyses: Introducing the Latin Hypercube Sampling technique

This study quantifies the effects of epistemic uncertainty in soil parameters on nonlinear (NL) site response analysis (SRA) results, validated against the data recorded at a well-instrumented geotechnical downhole array located in Japan. To this end, a one-dimensional soil column model of the Service Hall Array (SHA) near the Kashiwazaki-Kariwa Nuclear Power Plant (KKNPP) is developed using the finite element (FE) program LS-DYNA. The dynamic stress–strain relationship is characterized by a modified two-stage hyperbolic (MTH) NL backbone curve formulation capable of capturing soil behavior at both small- and large-shear strains. The model is then validated against the ground motion recordings to capture the model bias. The uncertainties associated with the shear-wave velocity profile (a small-strain soil property) and soil shear strength (a large-strain soil property) are incorporated in NL SRA to quantify their separate and joint randomization effects on the results. This study proposes using the Latin Hypercube Sampling (LHS) method as an efficient alternative to commonly used methods, such as Standard Monte Carlo (SMC), to account for uncertainty propagation in such reliability analysis. Both low-intensity and design-level records from the recordings at the SHA are applied to study the contribution of the small- and large-strain NL dynamic soil properties. Results from 46,200 NL FE analyses (23,100 per input motion) are presented. Measured and predicted site response, using recorded ground motions at this downhole array, is compared to assess the significance of soil parameter uncertainty on the observed ground motion dispersions. It is demonstrated that increasing the number of soft realizations and implementing higher level earthquake intensity lead to higher ground motion dispersion. Unlike past studies in randomization of Vs profiles with the SMC method, the LHS method is shown to have no significant effect on the predicted median surface response spectra and amplification factors (AFs) for this case study.

Stochastic stability analysis of particle swarm optimization with pseudo random number assignment strategy

Particle swarm optimization (PSO) is a population-based optimization method and has been successfully applied to solve many real-world problems. This method belongs to the stochastic optimization method and is mainly driven by two random streams utilized in the stochastic search mechanism, namely, individual (cognition) and social randomness effects. To our best knowledge, no research work has been conducted about the manipulation of the random stream assignment for stochastic search mechanism in the PSO algorithm. In this work, the influences of controlling randomness in the searching scheme of PSO is studied by introducing different pseudo random number (PRN) assignment strategies. The order-1 and order-2 stability analyses for particle dynamics under different PRN assignment strategies are also conducted to understand the influences. Stability analysis is carried out using the stochastic process theory. Our results show that the correlation caused by PRN has no effect on the unbiasedness of the expectation of particle position, but it would reduce or increase the variance of particle dynamics. Second, the convergent conditions of the PSO system under different PRN assignment strategies and the corresponding parameter selection ranges are provided. Finally, an empirical analysis via experimental simulations evaluated by six common swarm diversity measures, eight benchmark test functions, and two parameter tuples is presented.

Anti-neoplastic drugs for malignant pleural effusion in non-small cell lung cancer: A meta-analysis.

e21060 Background: Malignant pleural effusion (MPE) occurs in 7-23% of advanced non-small cell lung cancer (NSCLC) patients with overall survival (OS) of 8.5 months only. The optimum anti-neoplastic regimen in MPE is yet to be determined. Thus, we conducted a meta-analysis to determine the optimum anti-neoplastic agent in managing MPE in NSCLC. Methods: We searched PubMed, Scopus, CENTRAL, ASCO, ESMO, and IASLC meetings libraries to retrieve relevant trials. We included single-arm and controlled trials in which patients with MPE were treated by anti-neoplastic drugs such as chemotherapy and/or targeted therapy. Patients treated with radiotherapy were excluded. Primary and secondary endpoints were efficacy and safety, respectively. Meta-analysis was conducted for the primary endpoint estimated by OS and objective response rate (ORR). In addition, subgroup analysis was conducted to investigate the effect of route of administration (ROA) and randomization on ORR. Results: We included 11 trials with a total of 542 patients. There were 5 randomized clinical trials, 5 phase II trials, and 1 phase I trial with a total of 16 relevant arms. Five arms used single-agent chemotherapy (SC), 11 combined therapy (CT) and 6 arms bevacizumab-based (BEVA) therapy. The ROA was intrapleural (IP) in 10 arms and intravenous (IV) in 6 arms. We pooled 124 patients from 5 trials that reported ORR results for SC patients. The pooled ORR was 41.7% (95% CI: 32.8 to 50.8%) with no heterogeneity ( I2 = 0%, p = 0.47). Pooling of 396 patients who underwent CT in 10 studies results in an ORR of 64.1% (95% CI: 52.7 to 74.8%) with a high heterogeneity rate ( I2 = 84%, p&lt; 0.01). Analysis of BEVA studies yielded an ORR of 62.2% (95% CI: 43.5 to 79.2%), representing 133 patients from 5 trials. The table shows the effect of randomization and ROA on ORR. One-year OS was reported in 4 studies that used CT; pooled 1-year OS estimate for 216 patients was 81.2% (95% CI: 75.5 to 86.4%). As for grade 3/4 AEs, the occurrence of nausea/vomiting (N/V) was higher in CT than SC (14% vs 2%). Chest pain rate was similar (9.8% vs 7.0%), leukopenia was higher in BEVA than SC (19.1% vs 9.8%), and neutropenia was more prevalent in BEVA than CT (22.1% vs 8.1%). Incidence of any-grade N/V was more common in BEVA than SC (42.9% vs 19.3%). Conclusions: Both CT and BEVA-based regimens were effective and safe in treating MPE. IP was superior to IV in CC and BEVA based regimens. ORR was higher in randomized trials, suggesting a better response of MPE under optimum clinical conditions. Further trials of these agents are needed to confirm these results.[Table: see text]

Weak Randomness Analysis of Measurement-Device-Independent Quantum Key Distribution with Finite Resources

The ideal quantum key distribution (QKD) protocol requires perfect random numbers for bit encoding and basis selecting. Perfect randomness is of great significance to the practical QKD system. However, due to the imperfection of practical quantum devices, an eavesdropper (Eve) may acquire some random numbers, thus affecting the security of practical systems. In this paper, we analyze the effects of the weak randomness in the measurement-device-independent QKD (MDI-QKD) with finite resources. We analytically derive concise formulas for estimating the lower bound of the single-photon yield and the upper bound of the phase error rate in the case of the weak randomness. The simulation demonstrates that the final secret key rate of MDI-QKD with finite resources is sensitive to state preparation, even with a small proportion of weak randomness, the secure key rate has a noticeable fluctuation. Therefore, the weak randomness of the state preparation may bring additional security risks. In order to ensure the practical security of the QKD system, we are supposed to strengthen the protection of state preparation devices.

Effects of Carbon Policy on Carbon Emission Reduction in Supply Chain under Uncertain Demand

Although there are many articles on carbon emission reduction of sustainable supply chain, most of them study the carbon emission reduction efficiency of supply chain in the case of single carbon policy or demand determination. Based on previous studies, this paper considered a supply chain consisting of a single manufacturer and a single retailer in an uncertain demand market. The effects of demand randomness and different carbon policies on carbon emission reduction level and optimal decision in supply chain were studied by constructing mean-variance utility function and Stackelberg game. Due to the difficulty of data acquisition, this paper verified the equalization results by numerical simulation. The results show that: (1) cap-and-trade policy, government subsidy policy and carbon tax policy can promote the carbon emission reduction investment of supply chain, while carbon tax policy will lead to the decline of the overall profit of supply chain; (2) For the manufacturer and the retailer, adopting a strategy with a low degree of risk avoidance will increase its own profits; (3) For the supply chain as a whole, it is more advantageous for manufacturers to adopt higher risk avoidance strategies, while retailers to adopt lower risk avoidance strategies. In addition, in the conclusion, this paper puts forward management implications related to stakeholders, thus providing help for the development of sustainable supply chain.

Evaluating the behaviour of centrally perforated unreinforced masonry walls: Applications of numerical analysis, machine learning, and stochastic methods

The presence of openings greatly affects the response of unreinforced masonry (URM) walls. This topic greatly attracts the attention of many researchers. Perforated unreinforced masonry (PURM) walls under in-plane loads through the truss discretization method (TDM) along with several machine learning approaches such as Multilayer perceptron (MLP), Group of Method Data Handling (GMDH), and Radial basis function (RBF) are described in this paper. A new method named Multi-pier (MP) that is fast and accurate, is used to determine the behavior of PURM walls. The results of the MP method are expressed as a ratio of lateral load-bearing capacity and initial stiffness of PURM walls to the solid wall in order to generalize the obtained results to other PURM walls. The outcomes of the MP method are employed to predict the behavior of PURM walls using various machine learning approaches. Using the validated network with suitable accuracy, empirical functions and curves are presented in an effort to provide a simplified and practical approach to assess the reduction in the load-bearing capacity and initial stiffness of PURM walls. Results indicate that the adjacent piers of opening have a remarkable impact on the overall response of the PURM wall. Finally, the ability of the MP method to conduct stochastic analysis is evaluated. Moreover, the effect of randomness in the mechanical characteristics and their spatial variation within the PURM wall is presented.

Patient and Clinician Perspectives on Two Telemedicine Approaches for Treating Patients with Mental Health Disorders in Underserved Areas.

Primary care practices in underserved and/or rural areas have limited access to mental health specialty resources for their patients. Telemedicine can help address this issue, but little is known about how patients and clinicians experience telemental health care. This pragmatic randomized effectiveness trial compared telepsychiatry collaborative care, where telepsychiatrists provided consultation to primary care teams, to a referral approach, where telepsychiatrists and telepsychologists assumed responsibility for treatment. Twelve Federally Qualified Health Centers in rural and/or underserved areas in 3 states participated. Patients and clinicians reported that both interventions alleviated barriers to accessing mental health care, provided quality treatment, and offered improvements over usual care. Telepsychiatry collaborative care was identified as better for patients with difficulty developing trust with new providers. This approach also required more primary care involvement than referral care, creating more opportunities for clinician learning related to mental health diagnosis and treatment. The referral approach was identified as better suited for patients with higher complexity or desiring specific psychotherapies. Both approaches addressed patient needs and provided access to specialty mental health care. Each approach better aligned with different patients' needs, suggesting that having both approaches available to practices is optimal for supporting patient-centered care.

No Difference in the Acute Effects of Randomization vs. Blocking of Units of Lower-Extremity Proprioceptive Training on Balance and Postural Control in Young Healthy Male Adults.

Random practice is a form of differential learning and its favorable acute effects on motor performance are well described when visual tasks are practiced. However, no study to date has investigated the acute effects of differential learning using variable proprioceptive stimuli instead of the visual cues. The aim of the present study was to compare the acute effects of randomized versus blocked lower-extremity proprioceptive training stimuli on balance and postural adjustments. In two conditions, healthy young males (n = 15, age = 23 years) performed 16 one-legged landings on a board tilted in four directions: 1) tilt direction unknown and randomized and 2) tilt direction known with order of presentation blocked. Multi-segmental angular sway while balancing on an unstable surface and postural responses to perturbation stimulus by surface tilts were measured before and 4 min after training. Overall frontal-plane postural sway on the unstable surface decreased (p < 0.05, η2 = 0.022) in both conditions, while sagittal-plane postural sway remained unchanged. When the surface was toes-up tilted in the perturbation test, the sagittal-plane shank-thigh-pelvis alignment improved in both conditions (p < 0.05, η2 = 0.017), but the direction of the segmental positioning was non-uniform across participants. We conclude that randomization vs. blocking of units of lower-extremity proprioceptive training did not affect balance and postural control in our cohort of healthy young adults but the improvements were test-specific.

Random Serial Dictatorship for horizontal collaboration in logistics

In this paper, we propose the application of matching mechanisms to handle horizontal collaboration in logistics. Based on the requirements of a real-life setting, we introduce a new variation of matching under preferences. We provide a Random Serial Dictatorship (RSD) mechanism for finding a solution that incorporates Pareto optimality, incentive compatibility and fairness, which are desired properties for enabling collaboration between antagonistic participants. Further, we present an extensive experimental analysis that is twofold. We compare the proposed RSD mechanism to two well-known matching mechanisms, namely Maximising Cardinal Utilities (MAXCU) and Bundled Probabilistic Serial (BPS). We compare these mechanisms with respect to cardinal efficiency and envy, and highlight the complementarity between them for handling different settings. Most importantly, we show that RSD is the most appropriate choice for settings similar to the one motivating our study. Moreover, we examine the effect of randomisation of RSD to fairness. Finally, we discuss how our matching mechanism was applied in the real-life context of four 3rd Party Logistics providers. Results show that the proposed approach creates significant potential for synergies and may be used to support horizontal collaboration in logistics.

Fuzzy-Swarm Intelligence-Based Short-Term Load Forecasting Model as a Solution to Power Quality Issues Existing in Microgrid System

Load demand is highly stochastic and uncertain. This is because it was highly influenced by a number of variables like load type, weather conditions, time of day, the seasonality factor, economic constraints, and other randomness effects. The loads are categorized as holiday loads (national and religious), weekdays, and weekend days. The nonlinearity and uncertain characteristics of electrical load in a microgrid are one of the major sources of power quality problems in a microgrid system, and they can be handled using an accurate load forecast model. The fuzzy load prediction model can effectively handle these nonlinearity and uncertainty characteristics to have an accurate load forecast, but the main challenge with this model is its inability to accommodate a large volume of historical load and weather information when the membership function of the input and output fuzzy variables and the number of the fuzzy rules are tremendous. The swarm intelligence load forecast model based on particle swarm optimization algorithms can improve the limitations of the fuzzy system and increase its forecasting performance. The parameters of time, temperature, historical load, and error correction factors are considered as the Fuzzy and Fuzzy-PSO model input variables, while the forecasted industrial load is the only output variable. The Gaussian membership function is considered for both the input and output fuzzy variables. A 3-year historical hourly load data of an Ethiopian industrial system is used to train and validate both prediction models. The mean absolute percentage error (MAPE) is used to evaluate the performance of these prediction models. The Fuzzy-PSO load prediction model shows results that have superior performance to the fuzzy-alone load prediction results.