关键词： Hybrid algorithms   Intelligent optimization   Mathematical modeling   PSO-GA   Submerged arc welding  

摘要： In the original publication, the fourth author name was incorrectly published.

关键词： Color harmony algorithm   Global optimization   Metaheuristic   Population-based optimization  

摘要： In the last 3 decades, metaheuristic algorithms have received more popularity because of their superior performance to solve large and complex optimization problems. Most of these algorithms are inspired by biological phenomena, social behavior of animals, science and art. Among these four sources, the last one is utilized only by one algorithm. In this paper, we propose another novel art-inspired population-based metaheuristic, called color harmony algorithm (CHA), for solving the global optimization problems. The proposed method models its search behavior through combining harmonic colors based on their relative positions around the hue circle in the Munsell color system and harmonic templates. We utilize simultaneously four different fitness information to construct the hue groups, which improve search ability of the algorithm. CHA has two different phases including the concentration phase and the dispersion phase which are employed to explore and exploit the search space. The performance of the proposed method has been examined using several benchmark test functions commonly used in the literature. To show the effectiveness and robustness of the proposed method, the results are compared with those obtained using ten well-known metaheuristic algorithms. Also, the Wilcoxon Signed-Rank test is conducted to measure the pair-wise statistical performances of the algorithms. The results indicate that besides the simplicity of the proposed algorithm, CHA can outperform the other considered algorithms in terms of the convergence speed and the number of function evaluations. [ABSTRACT FROM AUTHOR]

关键词： Mixed-model assembly line   Human-robot collaboration   Bee algorithm   Artificial bee colony algorithm   Mixed-integer linear programming  

摘要： The collaboration of human workers and robots draws increasing attention from the manufacturing enterprises to embrace the Industry 4.0 paradigm in a competitive way. Motivated by the requirements of collaboration between human workers and robots in assembly lines, this study investigates the mixed-model assembly line balancing (MMALB) problem with the collaboration between human workers and robots. A mixed-integer linear programming (MILP) model is formulated to tackle the small-size problems optimally to minimize the sum of cycle times of models. Also, bee algorithm (BA) and artificial bee colony (ABC) algorithm are implemented and improved to solve the large-size problems due to the NP-hardness of this problem. The proposed BA algorithm utilizes a new employed bee phase to accelerate the evolution of the swarm and new scout phase to escape from being trapped into local optima and produce a high-quality and diverse population. The developed ABC proposes a new onlooker phase to accelerate the evolution of the whole swarm by removing the poor-quality solutions, new scout phase to achieve high-quality solutions while preserving the diversity of the swarm, and local search to enhance exploitation capacity. Computational study on a set of generated instances indicates that the improvements enhance the BA and ABC algorithm by a significant margin, and the proposed BA and ABC algorithm achieve competing performance in comparison with nine other algorithms, including the late acceptance hill-climbing algorithm, simulated annealing algorithm, genetic algorithm, particle swarm optimization algorithm, discrete cuckoo search algorithm, the original bee algorithm, and three artificial bee colony algorithms. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Metaheuristic optimization   Interactive autodidactic school   Mathematical optimization   Structural optimization  

摘要： A new efficient and robust metaheuristic algorithm called "Interactive Autodidactic School (IAS)" is proposed in this paper to solve numerical optimization and structural design optimization problems. IAS is a population-based algorithm on the basis of the interactions between students in an autodidactic school with the goal of increasing their knowledge through a combination of self-teaching/self-learning, interactive discussion, criticism, and the competition. IAS is tested in twenty mathematical optimization and seven structural optimization problems. Subsequently, its optimum solution is compared with other well-known optimization algorithms. The obtained results confirmed that the proposed IAS algorithm gives best optimal solution and has excellent performance compared with other optimization methods. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： 人脸识别   肤色建模   五官定位  

摘要： 为了人脸识别技术进一步快速定位人脸,改善了肤色色彩空间的聚合性多样复杂问题。本文提出了一种建立人脸位置的判断模型的方法,利用肤色色彩空间YCrCb建模,建立肤色高斯模型,进而得到黑白二值图,利用二值图计算单个像素的肤色相似性从而得到一个灰度图,较好解决肤色相似问题,缩小范围后进行眼睛、嘴巴精确定位,最终获得人脸定位。基于实验结果,此方法能有效识别人脸位置,且相较于以往方法更加简单可行。

关键词： 中职   计算机专业   数学课堂   算法教学  

摘要： 中职教育的专业划分更为精细,且对学生专业知识的掌握要求也更高,因此中职计算机专业的教学要求学生能够扎实地掌握计算机方面的理论知识与实操技能,数学作为计算机专业的基础课程,对专业的学习具有较大的影响作用,而算法教育更是计算机专业向更深层次学习的基础,对此我们要对中职计算机专业数学课堂的算法教学方法提高重视,不断探索算法教学的更好方法,以此来提高数学课堂算法的教学质量,进而保证学生对计算机相关知识的学习与掌握[1].

关键词： 小学   “算法多样化”   计算能力  

摘要： 算法多样化的思想强调的是尊重学生的独立思考,鼓励学生探索不同的方法,并不是让学生掌握多种方法,教师应该在课堂中鼓励、尊重学生思维的结果,引导学生进行讨论和交流,适时点拨,肯定有价值、有创意的方法,从而培养学生良好的思维习惯和探索创新的精神。

关键词： Ordinary differential equations   Postconditions   Preconditions   Invariants   Grobner bases  

摘要： A system of polynomial ordinary differential equations (odes) is specified via a vector of multivariate polynomials, or vector field, F. A safety assertion psi -> [F] phi means that the trajectory of the system will lie in a subset phi (the postcondition) of the state-space, whenever the initial state belongs to a subset psi (the precondition). We consider the case when phi and psi are algebraic varieties, that is, zero sets of polynomials. In particular, polynomials specifying the postcondition can be seen as a system's conservation laws implied by psi. Checking the validity of algebraic safety assertions is a fundamental problem in, for instance, hybrid systems. We consider a generalized version of this problem, and offer an algorithm that, given a user specified polynomial set P and an algebraic precondition psi, finds the largest subset of polynomials in P implied by psi (relativized strongest postcondition). Under certain assumptions on phi, this algorithm can also be used to find the largest algebraic invariant included in phi and the weakest algebraic precondition for phi. Applications to continuous semialgebraic systems are also considered. The effectiveness of the proposed algorithm is demonstrated on several case studies from the literature. (C) 2020 Elsevier B.V. All rights reserved.

关键词： 游戏教学法   小学数学   算法多样化   应用  

摘要： 《义务教育数学课程标准》(2011年版)指出数学教学必须关注口算,强化估算训练,并激励学生算法多样化。算法多样化是指教师在实际教学当中先要求学生经历探索研究的过程发现算法,在此基础之上展示算法,并由教师进行适当的补充和拓展,使学生深入感悟算理,形成与自身学习特点相符合的算法,使算法能服务于数学学习与生活,让学生感知数学的魅力。在实现算法多样化的过程中,引入游戏教学法更能唤起学生的求知欲和学习兴趣,促使学生释放个性,形成良好的学习精神。

关键词： 密集假目标干扰   频率捷变   最大类间方差法   数学形态学   二维稀疏重构  

摘要： 数字射频存储器(digital radio frequency memory,DRFM)通过截获雷达发射信号并对其进行调制和转发,在距离维上形成欺骗式干扰,严重影响了雷达对目标的检测与跟踪。针对这一问题,提出一种捷变频联合数学形态学的密集假目标干扰抑制算法。首先,采用最大类间方差法(Otsu)对脉冲压缩后的数据进行二值化处理。然后,通过数学形态学中的开运算抑制干扰和噪声。最后,通过二维稀疏重构获得距离速度二维高分辨,实现对目标的检测。仿真实验与实际雷达和干扰机对抗实验表明,该方法可以获得良好的抗干扰性能和目标检测性能。